Acknowledgments

The National Science Foundation funded the study through a grant to the University of Michigan (grant no. SES-2209438).

ANES Principal Investigators and staff designed the study and supervised data collection with input from the ANES advisory board and user community. The Principal Investigators were Nicholas Valentino at the University of Michigan and Shanto Iyengar at Stanford University. The Associate Principal Investigators were Sunshine Hillygus at Duke University and Daron Shaw at the University of Texas at Austin.

David Howell (University of Michigan) and Matthew DeBell (Stanford University) served as the study directors. The ANES staff on the project included Elora Choudhury, Lauren Guggenheim, Sang-Jung Han, Laurie Pierson, Rachel Smilan-Goldstein, and Jaime Ventura. Graduate student contributors were Avery Goods, Francy Luna Diaz, and Clinton Willbanks, while undergraduate support was provided by Junjie Li, Mallory Moore, and Phoebe Yi.

Data collection was performed by the Survey Research Operations (SRO) unit at the University of Michigan’s Survey Research Center (SRC), with support from SRC faculty. SRO developed the sampling plan and collaborated with ANES personnel on other aspects of the study’s technical design. Lead personnel on the project at SRO included Andrew Hupp, Grant Benson, Paul Burton, Theresa Camelo, Wen Chang, Stephanie Chardoul, Karl Dinkelmann, Raphael Nishimura, and Lisa Van Havermaet.

Marketing Systems Group provided the sampling frame.

USER GUIDE

This document is a brief guide and codebook for the American National Election Studies (ANES) 2024 Time Series Study, to accompany the full release of its pre-election and post-election data on May 19, 2026.

The ANES 2024 Time Series is a continuation of the series of election studies conducted since 1948 to support analysis of public opinion and voting behavior in U.S. presidential elections. The 2024 study features a mixed-mode design including in-person, internet, video, phone, and paper-and-pencil interviewing. Two separate fresh cross-sectional samples were drawn, one for use with in-person interviewing as the primary mode and the second for web interviewing as the primary mode. In addition, the 2024 study features a panel of respondents previously completed the ANES in 2016 and 2020, as well as interviews with individuals who previously participated in the 2024 General Social Survey (GSS).

How to Cite the Study

American National Election Studies. 2026. ANES 2024 Time Series Study Full Release [dataset and documentation]. May 19, 2026 version. www.electionstudies.org

Current Release

The current release (May 19, 2026) is a re-release of the 2024 Time Series study dataset with some important updates:

Corrected data due to misapplication of forward/reverse randomization in the following variables: V241352, V241353x, V241620, V242213, V242233, V242234x, V242243, V242244, V242245x, V242246, V242247, V242248x
Miscellaneous data corrections in the following variables: V241106x, V241445x, V242051
Missing data recode in variable V242020
Responses incorrectly coded -5 (breakoff) for case id 141189 and have been recoded to -1 (inapplicable) in the post-election data
Corrected value labels have been added to the following variable: V241004, V241287x, V241444x, V241445x, V242002, V242003, V242364x, and V242509a to V242509f
Unrestricted versions of variables V242530 to V242535 (IDENT) have been merged into the main dataset after having previously been available as a standalone data file
Data from the variables originating from the WEBSITES and INETNEWS items in the instrument have been temporarily removed to investigate a technical error in the data
Previously unreleased variables from the MIP submodule (coded responses for mention 1, mention 2, mention 3, and the most important problem) are now included in the dataset: V242165y1 to V242165y5, V242167y1 to V242167y5, V242169y1 to V242169y5, V242171y1 to V242171y5

If you find errors or have comments or questions about the data, please communicate with ANES staff by writing to [email protected]

Sample Design

The study has four independently drawn sample components:

1. Fresh sample for in-person interviews
2. Fresh sample for web interviews
3. Panel re-interviews
4. GSS re-interviews (not included in this release)

Another component of the study involved a brief interview with the spouses or partners of respondents in the fresh sample groups who were in spousal or cohabiting relationships.

Population. The two fresh samples for in-person and web interviews describe approximately the same population. The target population for the in-person sample was 232.5 million U.S. citizens age 18 or older living in the 48 contiguous states of the U.S. or Washington, D.C., and the target population for the web sample was 234.1 million U.S. citizens age 18 or older living in the 50 states or Washington, D.C. Both populations exclude those living in institutional or group quarters. In both modes, the sampling frame consisted of lists of residential addresses where mail is delivered. To be eligible to participate, a respondent had to reside at the sampled address and be a U.S. citizen aged 18 or older at the time of recruitment.

The ANES 2016-2020-2024 panel’s target population consisted of U.S. citizens who were 18 or older and living in the 50 states or Washington, D.C., immediately before the 2016 presidential election.

The General Social Survey’s target population was adult residents of the U.S. See GSS documentation for more information about GSS sampling. GSS re-interview data are not included in this data release and will be made available as a supplemental file.

Sample Design

Fresh in-person sample. The fresh in-person sample was a multi-stage stratified cluster sample. This is similar in general design, but different in details, from past designs of ANES Time Series studies. Sixty primary sampling units (PSUs) were selected from across the 48 contiguous states and Washington, D.C. The PSUs were metropolitan statistical areas (MSAs) or non-MSA counties, or combinations of counties, to achieve a minimum population of 50,000 adult citizens. PSUs were explicitly stratified by quintiles of county-level Republican vote share in 2020 and terciles of county-level turnout in 2020, and implicitly stratified by region, and then selected at random with probability proportional to the number of occupied housing units as indicated by the 2020 U.S. Census, except that Los Angeles County, CA, Cook County, IL, Harris County, TX, and Maricopa County, AZ, were selected with certainty.

Within each PSU, four smaller areas were drawn (secondary sampling units, which were Census Block Groups or groups of contiguous CBGs to form a minimum size of 100 occupied housing units), and households were selected at random from within these areas from the U.S. Postal Service’s computerized delivery sequence file (DSF).

These secondary sampling units were explicitly stratified by the proportion of owner-occupied housing units (above-median or below-median within the PSU) and implicitly by the proportion of college graduates. Finally, the in-person sample addresses were explicitly stratified by the predicted average turnout (four categories, including no voter file match) and implicitly stratified by the predicted probability of voting for Trump in 2020. Probability of a Trump vote was calculated by (1) estimating a LASSO logistic regression model using ANES 2020 data (regressing ANES 2020 self-reported 2020 Trump vote over multiple variables from the voter file at the respondent level, (2) using the estimated model with the retained variables to estimate the probability of 2020 Trump vote for each voter matched to addresses selected in the sample, and (3) computing the average of these estimated probabilities over voters at the same address.

Fresh web sample. The fresh web sample was selected from the DSF in two phases from among residential addresses in all 50 states and Washington, D.C. In the first phase, the frame was explicitly stratified by quintiles of county-level Republican vote share in 2020, terciles of county-level turnout in 2020, and four census regions. A total of 40,000 addresses were selected in this phase. Then, in the second phase, 6,800 addresses were selected, explicitly stratified by the phase 1 strata above and also by predicted address average turnout in 2020 and 2022, and implicitly stratified by the address’ average probability of a 2020 Trump vote.

Mode sample differences. The fresh in-person sample component of the study does not include respondents from Alaska or Hawaii, whereas the fresh web sample component does. This is the main substantive design difference in eligibility and coverage for the two fresh samples, and for most analytic purposes, it is probably ignorable because the combined population of Alaska and Hawaii is less than one percent of the study population.

Panel sample. Respondents who completed both the ANES 2016 and ANES 2020 studies were invited to participate again in the ANES 2024 study, except for a very small number of past respondents who opted out and asked not to be contacted again.

Respondent recruitment and retention

Pre-election study

Fresh in-person sample. An advance letter, including a study brochure and $5 in cash, was sent to each selected address. Following this, an interviewer visited the address to conduct a screening interview, which was used to randomly select one person from among the adult U.S. citizens living there to be invited for the 2024 interview. Those interviewed were given $25 or $50 during the initial phase of the field period, with the amount increasing to $100 after an initial non-response. Interviewers were authorized to offer $150 if necessary.

Fresh web sample. Selected addresses were sent a series of letters to recruit one household member to complete a screening survey. The initial invitation letter included $10 in cash and promised $40 for completing the online survey. The incentive was later escalated to $100 for initial non-respondents. The screening survey was used to randomly select one person from among the adult U.S. citizens living at the address to complete the 2024 questionnaire online.

In cases where the person who completed the screener was not selected to complete the 2024 questionnaire, they received either $40 or $100, as did the selected respondent after they completed the 2024 questionnaire. If the person who completed the screener was selected for the 2024 survey, they received one payment of $40 or $100 after completing both the screener and the 2024 questionnaire.

Panel sample. Panelists were invited by mail, email (when available), or both, and asked to complete the 2024 questionnaire online. Invitations included a prepaid $10 cash incentive with a promise of $40 for completing the survey, which later escalated to $100 after an initial non-response.

Spouse and partner survey. If a respondent in either of the fresh sample groups had a spouse or cohabiting partner, the spouse or partner was invited to complete a brief questionnaire, either by paper or online. Spouses/partners received immediate invitations to participate as soon as the respondent finished their survey. The in-person spouse/partner request was also accompanied by a $5 cash payment. If they were not immediately available, partners from both groups received written invitations. The web sample received an email invitation, and the in-person sample received a paper invitation left behind with the survey and $5 in cash enclosed. Both groups received an initial offer of $20 to complete the survey, which then escalated to $40. Reminders were sent to non-responding spouses/partners, accompanied by paper copies of the questionnaire. In-person non-responding partners were eventually sent web links to complete the survey. The spouse/partner survey was only administered during the pre-election study.

Post-election study

Respondents who completed a survey or a sufficient partial survey in the pre-election study were approached after the election and asked to complete a post-election survey. Potential post-election respondents were initially offered the same incentive amount they received for their pre-election survey. On January 1, 2025, incentive offers of $25 or $50 were increased to $100 for non-finalized in-person cases. On January 13, 2025, incentive offers of $40 were increased to $100 for non-finalized web cases. On January 16, 2025, incentive offers were updated to $200 for resistant non-finalized in-person cases.

Data Collection

Field dates. The ANES 2024 Time Series study conducted a pre-election survey between August 3, 2024, and November 5, 2024. Election Day was November 5, 2024. The study attempted to re-interview the same respondents using a post-election survey between November 7, 2024, and February 17, 2025.

Locations. Interviews in the face-to-face mode were usually conducted in respondents’ homes, but could also be conducted at any location convenient for the respondent. Video interviews and web surveys could be completed anywhere the respondent had internet access, whether on a computer or a mobile device. Phone surveys could be completed on any device that had phone service.

Table. The 2024 ANES Pre-Election and Post-Election Survey
Sample	Wave	Mode of Interview					N
Sample	Wave	Face-to-face	Phone	Video	Web	Paper-and-pencil	N
* Not included in the full release, but will be available as a supplemental file.
Fresh in-person	Pre-election	966	76				1,042
Fresh in-person	Post-election	354	227	344			925
Fresh web	Pre-election				2,063	245	2,308
Fresh web	Post-election				1,769	200	1,969
Panel	Pre-election				2,171		2,171
Panel	Post-election				2,070		2,070
GSS *	Pre-election				987 *		987 *
GSS *	Post-election				807 *		807 *

Modes of pre-election interview administration. Interviews in the face-to-face mode were conducted by trained interviewers using computer-assisted personal interviewing (CAPI) software on laptop computers. During a portion of the face-to-face interview, the respondent answered certain sensitive questions directly on the laptop computer, without the interviewer’s participation (known as computer-assisted self-interviewing or CASI). In the fresh web sample, panel sample, and GSS sample, respondents were eligible to complete the survey in the web mode. Toward the end of the field period, non-respondents in the fresh web sample received a highly abbreviated four-page paper-and-pencil (PAPI) questionnaire, and were able to complete the survey in either the web or paper-and-pencil mode. With the exception of n = 245 paper-and-pencil cases, all other respondents in the fresh web group completed the survey in the web mode. All panel and GSS respondents completed the survey via the web mode. All cases in the fresh in-person sample were initially invited to a face-to-face interview; however, in some cases, the interview was conducted partly or entirely by phone (n = 76) rather than face-to-face (n = 966).

Modes of post-election interview administration. All fresh web, panel, and GSS sample respondents from the pre-election survey were invited to complete the post-election survey using the same mode in which they completed the pre-election survey.

Most in-person sample respondents were offered the opportunity to complete the post-election survey by video. To be eligible to participate in the post-election study using the video mode, respondents had to both 1) have access to the internet at home, and 2) score lower than four on variable IW_RATE, indicating that they liked the pre-election interview. In-person sample respondents who were eligible to participate via video were asked to schedule an appointment during the post-election data collection period.

Respondents who were either not eligible for video, did not set a video appointment, or missed their video appointment received a face-to-face visit for the post-election study. In some cases, respondents in the in-person sample who could not be reached by video or face-to-face were subsequently interviewed by phone. Respondents completing the survey by video or phone had the questions from the CASI portion of the questionnaire read out loud to them by the interviewer.

Interview length. The median administration times for the pre-election interviews, not counting screening procedures, were approximately 93 minutes for the in-person sample, 63 minutes for the fresh web sample, and 72 minutes for the panel sample. The median administration times for the post-election interviews were approximately 99 minutes for the in-person sample, 68 minutes for the fresh web sample, and 71 minutes for the panel sample.

Languages. Interviews were conducted in English or Spanish.

Response Rates

Pre-election interviews were considered sufficient to be counted as completions for weighting and calculation of the response rate when the survey was administered at least to the self-reported gender question (SELFGEND_GENDTYP) at the beginning of the CASI section of the questionnaire (and following other demographic items). Post-election interviews were considered sufficient to be complete if the respondent completed the VOTE section of the instrument. In both the pre- and post-election studies, respondents completing the associated abbreviated paper-and-pencil questionnaire are also counted as sufficient completions.

The following response rates are calculated using the American Association for Public Opinion Research (AAPOR) formula for the minimum response rate, AAPOR Response Rate 1.

The pre-election response rate was 33.4 percent for the fresh in-person sample and 37.7 percent for the fresh web sample. The pre-election re-interview rate for the panel sample (conditional on previously completing the ANES 2016 and 2020 studies and being invited to the 2024 study) was 82.0 percent.

The overall post-election re-interview rate was 89.9 percent of pre-election respondents. The post-election re-interview rate for the fresh in-person sample was 88.8 percent and 85.3 percent for the fresh web sample. The post-election re-interview rate for the panel sample was 95.3 percent.

The pre-election response rates and post-election re-interview rates for the GSS sample will be reported in the supplemental release of those data.

Restricted Data Access

Some variables, including date of birth, the respondent’s ZIP code, and verbatim answers to open-ended questions, are coded “-3. Restricted access” on this public use dataset. Data for many of these variables can be obtained through a Restricted Data Access agreement. Please see the ANES website for more information.

Responses to a selection of open-ended questions are made available to the public after the responses have been redacted for confidentiality.

Data Analysis, Weights, and Variance Estimation

Analyses should be weighted to represent the U.S. adult citizen population accurately. Sampling error calculations should account for the complex sample design and the effects of weighting on variance.

The data can be analyzed using the combined fresh sample, the fresh in-person sample alone, or the fresh web sample alone.

Weight variable selection

The list below indicates which weight variable to use for different types of analyses with the full release data. In general, if any post-election data are used for an estimate (alone or in combination with pre-election data), a post-election weight variable should be used, while analyses using solely pre-election data should use a pre-election weight.

Weight	Use for analysis from the …
V240101a	Pre-election fresh in-person sample alone
V240101b	Post-election fresh in-person sample alone
V240102a	Pre-election fresh web sample alone
V240102b	Post-election fresh web sample alone
V240103a	Pre-election fresh samples (fresh in-person + fresh web)
V240103b	Post-election fresh samples (fresh in-person + fresh web)
V240104a	Pre-election fresh web sample + PAPI
V240104b	Post-election fresh web sample + PAPI
V240105a	Pre-election fresh sample (fresh in-person + fresh web + PAPI)
V240105b	Post-election fresh sample (fresh in-person + fresh web + PAPI)
V240106a	Pre-election panel alone
V240106b	Post-election panel alone
V240107a	Pre-election full sample (fresh in-person + fresh web + panel) + PAPI
V240107b	Post-election full sample (fresh in-person + fresh web + panel) + PAPI
V240108a	Pre-election full sample (fresh in-person + fresh web + panel)
V240108b	Post-election full sample (fresh in-person + fresh web + panel)

Sampling errors and significance testing

The study is not a simple random sample, so statistical procedures for complex sample designs must be used to obtain correct estimates of sampling errors and correct indications of statistical significance. Statistical software such as Stata, R with a survey analysis package, or SPSS with the Complex Samples package can perform a Taylor Series estimation of sampling errors when provided with the appropriate strata and cluster variables. In Stata, the command to set up this type of analysis is as follows:

svyset [pweight=WEIGHT], psu(CLUSTER) strata(STRATA)

In the code example above, WEIGHT would be replaced with the correct weight for the type of analysis being performed (as indicated in the previous section on weighting). STRATA and CLUSTER would be replaced with the variables for the corresponding analysis, as shown below.

For weight	use variance PSU	and use variance stratum
V240101a	V240101c	V240101d
V240101b	V240101c	V240101d
V240102a	V240102c	V240102d
V240102b	V240102c	V240102d
V240103a	V240103c	V240103d
V240103b	V240103c	V240103d
V240104a	V240104c	V240104d
V240104b	V240104c	V240104d
V240105a	V240105c	V240105d
V240105b	V240105c	V240105d
V240106a	V240106c	V240106d
V240106b	V240106c	V240106d
V240107a	V240107c	V240107d
V240107b	V240107c	V240107d
V240108a	V240108c	V240108d
V240108b	V240108c	V240108d

For example, the code to set up Stata for an analysis of the full sample is as follows:

svyset [pweight=V240107a], psu(V240107c) strata(V240107d)

For more information about weighted analysis of ANES data, see DeBell, How to Analyze ANES Survey Data: http://www.electionstudies.org/Library/papers/nes012492.pdf

A note on subpopulation analysis or analysis with missing data

When conducting design-consistent variance estimation, cases should be selected by designating a subpopulation for the analysis procedure, not by dropping cases from the analysis or excluding missing data listwise. For some analyses the estimated standard errors from these two methods may be the same, or nearly so, but in other circumstances, failing to designate a subpopulation makes the standard error estimates incorrect. Also, in some cases, failing to designate a subpopulation may prevent the calculation of standard errors altogether by reducing the number of cases in a stratum to one. If, for example, Stata’s output omits standard errors and includes the note, “Missing standard errors because of stratum with single sampling unit,” this is usually because the user has dropped cases (explicitly or through extensive listwise deletion) instead of designating a subpopulation. Designating a subpopulation will solve the problem. In brief, this means using code of the following general form (for proportions from a single variable, in Stata):

svy, subpop(INCLUDE):prop VAR

In this example, INCLUDE is the name of a variable you generate to identify the subpopulation (with included cases coded 1 and excluded case coded 0) and VAR is the name of the variable for which proportions are generated. Similarly, you may use:

svy, subpop(if VAR >=1 & VAR <=5): prop VAR

This example selects cases conditional on VAR having values from 1 through 5. Other statistical software, such as R and SPSS, have comparable procedures. For more information about this kind of procedure, see the How To Analyze ANES Survey Data document linked above or the documentation for the statistical software you use.

A note on weights and modes

The weights are organized by sample group, which is distinct from the mode of interview. As detailed above in the Data Collection section, the fresh in-person sample includes interviews conducted in-person, by telephone, and over live two-way video. Weighting using the “in-person weight” selects the in-person sample, not only face-to-face interviews. Sample and mode can be identified (variables V240002a, V240002b and V240003), but within sample groups, the mode of interview was not randomly assigned, so analysts should be cautious about making mode comparisons or attributing differences among modes of interview to the interview mode itself; apparent mode differences may also be due to selection effects.

Reporting weighted sample sizes

When reporting the sample size (n) for an analysis, the actual, unweighted sample sizes should be reported, and analysts should take care not to confuse weighted sample sizes with unweighted sample sizes. Some statistical software applications make this distinction more readily than others. Generally, software designed for design-consistent survey estimation will report actual sample sizes, but software using non-survey procedures (such as frequency weights) will not. When frequency weights are used, the weighted sample size usually does not reflect the actual number of cases used in an analysis procedure (because weights vary, most analyses will exclude one or more cases due to selection criteria, listwise deletion or both, and the sums of subgroup weights are not constrained to sum to the actual sample size). In this case, in addition to running a weighted analysis, it is necessary to also run an unweighted analysis (taking care to select the same cases) in order to obtain correct sample sizes.

Weighting methods

The weights were computed in multiple steps to account for sample design features and to reduce various non-sampling error sources. The in-person and web pre-election surveys used a similar approach, as follows. Design weights were calculated to account for address sampling probabilities and the within-household selection of a single eligible adult. An adjustment was also performed to handle addresses whose eligibility was not able to be determined, redistributing their design weights to the remaining addresses with a known eligibility from their same corresponding stratum. To address both screening and main survey non-response, a propensity stratification approach was used for each component. In this approach, the probability of each eligible address to complete the survey was estimated using a logistic regression model of survey response over a set of covariates observed for both respondents and non-respondents. The eligible addresses were then divided into deciles of their estimated response propensities and the inverse of the average of these propensities for each decile was used as a non-response adjustment factor. Finally, a calibration adjustment was applied to ensure that the weighted sample distribution matched the population distribution with respect to various characteristics.

Upon some modelling of 2024 turnout and vote choice using ANES data, the following dimensions were ultimately selected to be used in the calibration:

Race by sex;
Marital status by sex;
Educational attainment by age,
Educational attainment by region;
Income by race/ethnicity;
Home tenure;
Nation of birth;
Population density;
Education attainment by metropolitan status.

The following variables (and categories) were used for the calibration:

Sex (male, female)
Age (18-29, 30-44, 45-59, 60 years or older)
Educational attainment (less than high school graduate, high school graduate, some college, college degree, graduate degree)
Race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic other)
Home tenure (home owner, other)
Nation of birth (U.S. born, foreign born)
Marital status (married, widowed, divorced or separated, never married)
Household income (less than $40,000, $40,000-$74,999, $75,000-$124,999, $125,000 or more)
Population density (less than 471 people/square mile, 471-2,377 people/square mile, 2,377-5,505 people/square mile, more than 5,505 people/square mile)
Metropolitan status (non-metropolitan, metropolitan)

Missing values in calibration variables were imputed for the purposes of weighting. Population benchmarks (control totals) were based on the 2023 American Community Survey 1-year estimates, except for population density, which was from the 2020 census, and metropolitan status, which was from the March supplement of the 2024 Current Population Survey.

To reduce weighting variability, the final weights were bounded at 5 times the average of their corresponding unbounded calibrated weights.

The panel survey used a similar approach, except that it started with the 2020 ANES final weights as an input weighting variable and only the main survey non-response adjustment and calibration procedure were applied, as the other adjustments were already embedded in the input weight.

Weights for various combinations of the samples (such as weights for the entire sample, or for the in-person and web combined) received two additional adjustments. First, the samples were integrated using a Hartley estimator composite factor. In this process, each sample received a composite factor θ (with 0 < θ < 1) proportional to the mean square error of their corresponding estimate for the proportion of Trump voters in the 2024 election. The mean square error was estimated using an estimate of bias and sampling variance. The bias was estimated as the difference between the sample estimate of Trump voter proportions and the true value according to the election results. The sampling variance estimate used respondent data accounting for all the design features, including weights, stratification, and clustering. Second, an additional calibration adjustment, following the same specifications as the initial calibration, was applied over the combined sample.

Orientation to the Data and Documentation

Dataset

The ANES 2024 Time Series Study Full Release is available in multiple file formats: SPSS (.sav), Stata (.dta), Comma Separated Values (.csv), and a fixed-width raw data file that can be read into SAS, SPSS, and Stata using syntax statements that have been provided.

Variables are stored using formats optimized for their data type. Missing data are coded as negative numbers, for instance, “-8. Don’t know”.

Along with the dataset, users should also download and make use of the two following pieces of documentation:

Questionnaire

The first piece of documentation is the Questionnaire, a document that provides information about each of the questions that were asked in the main survey. The questions in the Questionnaire are presented in the order they were asked. The Questionnaire includes the following information, where applicable, for each question: the section in which the question appears, question name, question wording, universe (where only a subset of respondents was to receive the question, which respondents those should be), and response options.

In addition to the Questionnaire, ANES separately provides the PAPI (paper-and-pencil) and SPS (Spouse and Partner Survey) survey questionnaires in PDF format. Both documents are available for download from the 2024 Time Series study page of the ANES website.

User Guide and Codebook

The second piece of documentation is the User Guide and Codebook. You are currently reading the User Guide, which provides a brief overview of the study and how to use its data and documentation.

The remainder of this file, after the User Guide, consists of the Codebook. Whereas the Questionnaire provides information about the questions asked in the survey, the Codebook provides information about the variables that appear in the dataset.

Questions and variables do not always have a one-to-one relationship. For instance, multiple questions may be combined into a single summary variable. Or various variables may be derived from a single question. Furthermore, not all variables have associated questions — for example, administrative variables.

The Codebook includes the following information, where applicable, for each variable: the variable name (all variable names start with a “V”, and summary variables end with the suffix “x”), variable label (with “PRE:” indicating that it is from the pre-election study), simplified question wording, response/code values and meanings, associated survey question(s), universe (where only a subset of respondents appear in a variable, which respondents those should be; note that universes are not included for most summary variables), information about whether randomization was used, and interviewer instructions.

CODEBOOK: VARIABLES

GENERAL NON‐SURVEY VARIABLES

Value Labels

ANES2024TimeSeries_20260519

Value Labels

-1. Inapplicable, did not participate in 2000 Time Series study

Value Labels

-1. Inapplicable, R did not participate in 2016 Time Series Study

Value Labels

1. Face-to-face (FTF)
2. Internet (WEB)
3. Paper (PAPI)
4. Phone

Value Labels

-7. Insufficient parital, interview deleted
-6. No post interview
1. Face-to-face (FTF)
2. Internet (WEB)
3. Paper (PAPI)
4. Phone
5. Video

Variable Note

This variable captures the mode in which the respondent completed the majority of the post-election survey. Some respondents did use multiple modes to complete the post-election survey.

Value Labels

1. Completed pre-election interview only
2. Completed pre and post-election interviews

Value Labels

1. Panel (2016-20-24)
2. Fresh sample (WEB)
3. Fresh sample (FTF)
4. GSS

WEIGHTING VARIABLES

PRE‐ ELECTION SURVEY VARIABLES

Question

Would you like to complete this survey in English or Spanish?

¿Quisiera completar esta encuesta en inglés o español?

Value Labels

-9. Refused
-1. Inapplicable
1. English / Ingles
2. Spanish / Espanol

Survey Question(s)

START_LANGUAGESELECT

Question

This interview may be monitored for training and data quality purposes.

Value Labels

-1. Inapplicable
1. Continue with audio recording
2. Continue do not record

Survey Question(s)

CONSENT_AUDCONS

Universe

IF INTERVIEW TYPE IS FACE-TO-FACE:

Question

IS THE RESPONDENT A MAN OR A WOMAN? IF UNSURE, CODE DK.

Value Labels

-8. Don’t know
-1. Inapplicable
1. Man
2. Woman

Survey Question(s)

GEND_GENDOBS

Universe

IF INTERVIEW TYPE IS FACE-TO-FACE OR VIDEO:

Question

How often do you pay attention to what’s going on in government and politics? [Always, most of the time, about half the time, some of the time, or never / Never, some of the time, about half the time, most of the time, or always]?

Value Labels

-9. Refused
-4. Error
1. Always
2. Most of the time
3. About half the time
4. Some of the time
5. Never

Survey Question(s)

CAMPINT_POLATTREV, Q4

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Some people don’t pay much attention to political campaigns. How about you? Would you say that you have been [very much interested, somewhat interested or not much interested/ not much interested, somewhat interested or very much interested] in the political campaigns so far this year?

Value Labels

-9. Refused
-1. Inapplicable
1. Very much interested
2. Somewhat interested
3. Not much interested

Survey Question(s)

CAMPINT_CAMPINTSTD

Response Order

Forward/Reverse order

Question

Do you approve or disapprove of the way the Democratic party handled choosing a new presidential candidate?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESREPL_PTYAPPR

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESREPL_PTYAPPRSTR

Universe

IF R APPROVES OF HOW DEM PARTY HANDLED CHOOSING NEW CANDIDATE /
IF R DISAPPROVES OF HOW DEM PARTY HANDLED CHOPSING NEW CANDIDATE:

Value Labels

-2. DK/RF in V241006 or V241007
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESREPL_PTYAPPR, PRESREPL_PTYAPPRSTR

Value Labels

-1. Inapplicable
1. Harris / Trump
2. Trump / Harris

Value Labels

-1. Inapplicable
0. Sample address not preloaded
1. Sample address preloaded

Question

Now on a different topic. Are you registered to vote?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_REGSTATUS

Universe

IF R’S PRELOAD ADDRESS IS NOT IN NORTH DAKOTA:

Question

Are you registered to vote? Mark one answer that best describes you.

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Not registered and do not intend to register
2. Not registered but intend to register
3. Registered as a Democrat
4. Registered as a Republican
5. Registered with another party
6. Registered with no party, or unsure which party

Survey Question(s)

PAPI PRE Q5

Question

I’d like to ensure that our records are accurate for election-related questions. The following is the address we currently have on file for you:

[Respondent’s preloaded address]

Is the following location the one you use for voting?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes, this is the correct address
2. No, this is not the correct address

Survey Question(s)

PREVOTE_ADDR

Question

Do you live at [Address on File] or somewhere else?

Value Labels

-9. Refused
-1. Inapplicable
1. I live here
2. I live somewhere else

Survey Question(s)

PAPI PRE Q1

Question

What is the address you use for voting?

Value Labels

-3. RESTRICTED [STAFF ONLY]

Survey Question(s)

PREVOTE_NEWADDR

Universe

IF PRELOAD ADDRESS IS NOT THE ADDRESS FOR VOTING:

Question

It appears that the state name is missing from the address you provided. In what state is your address for voting?

Value Labels

-1. Inapplicable
1. Alabama  2. Alaska  4. Arizona
5. Arkansas  6. California  8. Colorado
9. Connecticut  10. Delaware
11. District of Columbia (Washington DC)
12. Florida  13. Georgia   15. Hawaii
16. Idaho   17. Illinois   18. Indiana
19. Iowa   20. Kansas   21. Kentucky
22. Louisiana   23. Maine   24. Maryland
25. Massachusetts   26. Michigan   27. Minnesota
28. Mississippi   29. Missouri   30. Montana
31. Nebraska   32. Nevada   33. New Hampshire
34. New Jersey   35. New Mexico   36. New York
37. North Carolina   38. North Dakota   39. Ohio
40. Oklahoma   41. Oregon   42. Pennsylvania
44. Rhode Island   45. South Carolina   46. South Dakota
47. Tennessee   48. Texas   49. Utah
50. Vermont   51. Virginia   53. Washington
54. West Virginia   55. Wisconsin   56. Wyoming

Survey Question(s)

PREVOTE_NEWWHST

Universe

IF R DID NOT PROVIDE STATE NAME WHEN ASKED FOR NEW ADDRESS:

Value Labels

-1. Inapplicable
1. Registration address given

Survey Question(s)

PREVOTE_NEWADDR

Value Labels

-1. Inapplicable
0. State not included with registration address
1. State included with registration address

Survey Question(s)

PREVOTE_NEWADDR

Value Labels

-1. Inapplicable
1. City included with registration address

Survey Question(s)

PREVOTE_NEWADDR

Question

How many years have you been registered to vote at [this/that] address? If you are not sure, please use your best guess.

Value Labels

-3. RESTRICTED

Survey Question(s)

PREVOTE_REGYRS

Universe

IF R IS REGISTERED:
IF R’S NEW STATE OF RESIDENCE IS NOT NORTH DAKOTA:

Value Labels

-1. Inapplicable
0. State of registration not the same as sample state
1. State of registration the same as sample state

Value Labels

Question

Some people register to vote under their full name and others use different versions of their name. Others might have changed their name since they registered.

What about you? Under what name are you registered to vote?

Value Labels

-3. RESTRICTED [STAFF ONLY]

Survey Question(s)

PREVOTE_REGNAME

Universe

IF R IS REGISTERED:
IF R’S NEW STATE OF RESIDENCE IS NOT NORTH DAKOTA:

Question

What political party are you registered with, if any?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Democratic party
2. Republican party
4. None or independent
5. Another party {SPECIFY}

Survey Question(s)

PREVOTE_REGPTY

Universe

IF R IS REGISTERED TO VOTE IN STATE WHERE PARTY MAY BE REGISTERED:

Value Labels

-3. RESTRICTED

Value Labels

-1. Inapplicable
0. No Senate race in state of registration
1. Senate race in state of registration

Value Labels

-1. Inapplicable
0. No Governor race in state of registration
1. Governor race in state of registration

Value Labels

-1. Inapplicable
0. No party registration in s tate of registration
1. Party registration in state of registration

Question

Do you intend to register to vote before the November 5 elections, or do you not intend to register?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes, intend to register
2. No, do not intend to register

Survey Question(s)

PREVOTE_REGINT

Universe

IF R SAID NOT REGISTERED OR DK IF REGISTERED TO VOTE:
IF R’S NEW STATE OF RESIDENCE IS NOT NORTH DAKOTA:

Question

Did you vote in a Presidential primary election or caucus this year?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes, voted in Democratic primary or caucus
2. Yes, voted in Republican primary or caucus
3. No, didn’t vote in a primary or caucus

Survey Question(s)

PREVOTE_PRIMV

Question

In the Democratic Presidential primary or caucus, who did you vote for?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Joe Biden
2. Dean Phillips
3. Another Democrat
9. None of these candidates/uncommitted/left blank

Survey Question(s)

PREVOTE_PRIMVWHOD

Universe

IF R VOTED IN A DEMOCRATIC PRESIDENTIAL PRIMARY OR CAUCUS:

Question

In the Republican Presidential primary or caucus, who did you vote for?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Donald Trump
2. Ron DeSantis
3. Nikki Haley
4. Vivek Ramaswamy
5. Another Republican
9. None of these candidates/uncommitted/left blank

Survey Question(s)

PREVOTE_PRIMVWHOR

Universe

IF R VOTED IN REPUBLICAN PRESIDENTIAL PRIMARY OR CAUCUS:

Question

In the presidential primary or caucus, who did you vote for, or did you not vote?

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Didn’t vote in primary or caucus
2. Joe Biden
3. Another Democrat
4. Donald Trump
5. Nikki Haley
6. Another Republican

Survey Question(s)

PAPI PRE Q6

Question

This next question is not about the primary elections and caucuses that were held a few months ago.

Instead, we’d like to ask you about the election for President to be held on November 5, in which [Donald Trump is running against Kamala Harris / Kamala Harris is running against Donald Trump].

Have you already voted in that election, or have you not voted?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Have voted
2. Have not voted

Survey Question(s)

PREVOTE_VOTED

Randomization

Order of names in question text

Question

Just to be clear, I’m recording that you already voted in the election that is scheduled to take place on November 5. Is that right?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes, voted
2. No, have not voted

Survey Question(s)

PREVOTE_VCONF

Universe

IF R INDICATED VOTED EARLY IN THE 2024 GENERAL ELECTION:

Question

Which one of the following best describes how you voted?

- Definitely voted in person at a polling place before election day
- Definitely voted by mailing a ballot before election day
- Definitely voted in some other way
- Not completely sure whether I voted or not

Value Labels

-1. Inapplicable
1. Definitely voted in person at a polling place before election day
2. Definitely voted by mailing a ballot before election day
3. Definitely voted in some other way
4. Not completely sure whether I voted or not

Survey Question(s)

PREVOTE_HOWVOTE

Universe

IF R CONFIRMED ALREADY VOTED FOR THE 2024 GENERAL ELECTIONS:

Question

How about the election for President? Did you vote for a candidate for President?

Value Labels

-1. Inapplicable
1. Yes, voted for President
2. No, didn’t vote for President

Survey Question(s)

PREVOTE_PRESVT

Universe

IF R REPORTED THAT R VOTED:

Question

Who did you vote for? [ Kamala Harris (Democrat), Donald Trump (Republican) / Donald Trump (Republican), Kamala Harris (Democrat)], Robert F. Kennedy Jr. (Independent), Cornel West (Independent), Jill Stein (Green), or someone else?

Value Labels

-9. Refused
-1. Inapplicable
1. Kamala Harris
2. Donald Trump
3. Robert F. Kennedy, Jr.
4. Cornel West
5. Jill Stein
6. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_PRESVTWHO

Universe

IF R VOTED FOR PRESIDENT:

Randomization

Order of names in question text according to value in var candidateorder.
Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_PRESVTWHO

Universe

IF R VOTED FOR PRESIDENT:

Randomization

Order of names in question text according to value in var candidateorder.
Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Would you say your preference for this candidate was strong or not strong?

Value Labels

-1. Inapplicable
1. Strong
2. Not strong

Survey Question(s)

PREVOTE_PRESSTR

Universe

IF R ANSWERED WHICH PRESIDENTIAL CANDIDATE THEY VOTED FOR:

Question

How long before Election day did you decide that you were going to vote the way you did?

Value Labels

-8. Don’t know
-1. Inapplicable
1. 0-2 weeks
2. 3-4 weeks
3. 2 months
4. 3 months
5. 4 months
6. 5 months
7. 6+ months

Survey Question(s)

PREVOTE_VTPRESDEC

Universe

IF R ANSWERED WHICH PRESIDENTIAL CANDIDATE THEY VOTED FOR:

Question

Do you intend to vote in the November election for President?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_INTPRES

Universe

IF R DID NOT VOTE EARLY IN THE 2024 GENERAL ELECTIONS:

Question

Who do you think you will vote for? [ Kamala Harris (Democrat), Donald Trump (Republican) / Donald Trump (Republican), Kamala Harris (Democrat)], Robert F. Kennedy Jr. (Independent), Cornel West (Independent), Jill Stein (Green), or someone else?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Kamala Harris
2. Donald Trump
3. Robert F. Kennedy, Jr.
4. Cornel West
5. Jill Stein
6. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_INTPRESWHO

Universe

IF R DID NOT VOTE BUT INTENDS TO VOTE IN THE ELECTION FOR PRESIDENT:

Randomization

Order of names in question text according to value in var candidateorder.
Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_INTPRESWHO

Universe

IF R DID NOT VOTE BUT INTENDS TO VOTE IN THE ELECTION FOR PRESIDENT:

Randomization

Order of names in question text according to value in var candidateorder.
Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Would you say your preference for this candidate is strong or not strong?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strong
2. Not strong

Survey Question(s)

PREVOTE_INTPRESST

Universe

IF R ANSWERED WHICH PRESIDENTIAL CANDIDATE THEY INTENDED TO VOTE FOR:

Question

Do you prefer one of the candidates in the November election for President?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_PREFPRES

Universe

IF R DID NOT SAY THEY INTENDED TO VOTE FOR PRESIDENT:

Question

Who do you prefer? [ Kamala Harris (Democrat), Donald Trump (Republican) / Donald Trump (Republican), Kamala Harris (Democrat)], Robert F. Kennedy Jr. (Independent), Cornel West (Independent), Jill Stein (Green), or someone else?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Kamala Harris
2. Donald Trump
3. Robert F. Kennedy, Jr.
4. Cornel West
5. Jill Stein
6. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_PREFPRWHO

Universe

IF R DID NOT INTEND TO VOTE FOR PRESIDENT BUT PREFERS A PRESIDENTIAL CANDIDATE:

Randomization

Order of names in question text according to value in var candidateorder.
Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_PREFPRWHO

Universe

IF R DID NOT INTEND TO VOTE FOR PRESIDENT BUT PREFERS A PRESIDENTIAL CANDIDATE:

Randomization

Order of names in question text according to value in var candidateorder.
Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Donald Trump
2. Kamala Harris
3. Robert F. Kennedy
4. Cornel West
5. Jill Stein
6. Another candidate
7. No preference

Survey Question(s)

PAPI PRE Q7

Question

Would you say your preference for this candidate is strong or not strong?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strong
2. Not strong

Survey Question(s)

PREVOTE_PREFPRSTR, PAPI PRE Q8

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF R ANSWERED WHICH PRESIDENTIAL CANDIDATE THEY PREFERRED:

Question

If the election were just between Kamala Harris (Democrat) and Donald Trump (Republican) / Donald Trump (Republican) and Kamala Harris (Democrat), who would you vote for, or would you not vote?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
1. Kamala Harris
2. Donald Trump
3. Would not vote

Survey Question(s)

PREVOTE_VTPRES2, PAPI PRE Q9

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of names in question text according to value in var candidateorder.
Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for the House of Representatives in Washington D.C.? Did you vote for a candidate for the U.S. House of Representatives?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Yes, voted for House of Representatives
2. No, didn’t vote for House of Representatives

Survey Question(s)

PREVOTE_VOTEHS

Universe

IF R REPORTED THAT R VOTED:

Question

What is the party of the House candidate you voted for?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Democratic Party
2. Republican Party
5. Another party {SPECIFY}

Survey Question(s)

PREVOTE_HSVTWHO

Universe

IF R VOTED FOR U.S. HOUSE OF REPRESENTATIVES:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

What is the party of the House candidate you voted for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_HSVTWHO

Universe

IF R VOTED FOR U.S. HOUSE OF REPRESENTATIVES:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for the House of Representatives in Washington D.C.? Do you intend to vote in the election for the U.S. House of Representatives?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_INTHS

Universe

IF R DID NOT VOTE EARLY IN THE CURRENT YEAR GENERAL ELECTIONS:

Question

What is the party of the House candidate you think you will vote for?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Democratic Party
2. Republican Party
5. Another party {SPECIFY}

Survey Question(s)

PREVOTE_INTHSWHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE IN THE ELECTION FOR THE U.S. HOUSE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

What is the party of the House candidate you think you will vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_INTHSWHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE IN THE ELECTION FOR THE U.S. HOUSE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Do you prefer one of the candidates for the U.S. House of Representatives?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_HSPREF

Universe

IF R DID NOT SAY THEY INTENDED TO VOTE FOR U.S. HOUSE:

Question

What is the party of the House candidate you prefer?

Value Labels

-9. Refused
-1. Inapplicable
1. Democratic Party
2. Republican Party
5. Another party {SPECIFY}

Survey Question(s)

PREVOTE_HSPREFWHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR U.S. HOUSE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

What is the party of the House candidate you prefer?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_HSPREFWHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR U.S. HOUSE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for the United States Senate? Did you vote for a candidate for the U.S. Senate?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Yes, voted for Senate
2. No, didn’t vote for Senate

Survey Question(s)

PREVOTE_VOTESEN

Universe

IF R REPORTED THAT R VOTED:
IF A SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who did you vote for?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent Senate candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_VTSENWHO

Universe

IF R VOTED FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_VTSENWHO

Universe

IF R VOTED FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for the United States Senate? Do you intend to vote in the election for the U.S. Senate?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_INTSEN

Universe

IF R DID NOT VOTE EARLY IN THE CURRENT YEAR GENERAL ELECTIONS:
IF A SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who do you think you will vote for?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent Senate candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_INTSENWHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who do you think you will vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_INTSENWHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Do you prefer one of the candidates for the U.S. Senate?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_SENPREF

Universe

IF R DID NOT SAY THEY INTENDED TO VOTE FOR U.S. SENATE:

Question

Who do you prefer?

Value Labels

-9. Refused
-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent Senate candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_SENPREFWHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR U.S. SENATE:
IF PRELOAD CANDIDATE NAMES FOR R’S STATE CAN BE USED:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who do you prefer?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_SENPREFWHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR U.S. SENATE:
IF PRELOAD CANDIDATE NAMES FOR R’S STATE CAN BE USED:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the special election for the United States Senate seat now held by the Republican Pete Ricketts? Did you vote for a candidate for the U.S. Senate?

Value Labels

-1. Inapplicable
1. Yes, voted for Senate
2. No, didn’t vote for Senate

Survey Question(s)

PREVOTE_VOTESEN2

Universe

IF R REPORTED THAT R VOTED:
IF A SPECIAL SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who did you vote for?

Value Labels

-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent Senate candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_VTSEN2WHO

Universe

IF R VOTED IN U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_VTSEN2WHO

Universe

IF R VOTED IN U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the special election for the United States Senate seat now held by the Republican Pete Ricketts? Do you intend to vote in the election for the U.S. Senate?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_INTSEN2

Universe

IF R DID NOT VOTE EARLY IN THE CURRENT YEAR GENERAL ELECTIONS:
IF A SPECIAL SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who do you think you will vote for?

Value Labels

-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent Senate candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_INTSEN2WHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE IN U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who do you think you will vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_INTSEN2WHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE IN U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Do you prefer one of the candidates for the U.S. Senate?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_SENPREF2

Universe

IF R DID NOT SAY THEY INTENDED TO VOTE IN U.S. SPECIAL SENATE ELECTION:

Question

Who do you prefer?

Value Labels

-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent Senate candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_SENPREF2WHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who do you prefer?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_SENPREF2WHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for Governor? Did you vote for a candidate for Governor?

Value Labels

-1. Inapplicable
1. Yes, voted for governor
2. No, didn’t vote for governor

Survey Question(s)

PREVOTE_VOTEGOV

Universe

IF R REPORTED THAT R VOTED:
IF A GUBERNATORIAL RACE WAS HELD IN STATE OF REGISTRATION:

Question

Who did you vote for?

Value Labels

-9. Refused
-1. Inapplicable
1. Democratic Gubernatorial candidate
2. Republican Gubernatorial candidate
3. Indpendent Gubernatorial candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_VTGOVWHO

Universe

IF R VOTED FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_VTGOVWHO

Universe

IF R VOTED FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for Governor? Do you intend to vote for a candidate for Governor?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_INTGOV

Universe

IF R DID NOT VOTE EARLY IN THE CURRENT YEAR GENERAL ELECTIONS:
IF A GUBERNATORIAL RACE WAS HELD IN STATE OF REGISTRATION:

Question

Who do you think you will vote for?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Democratic Gubernatorial candidate
2. Republican Gubernatorial candidate
3. Indpendent Gubernatorial candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_INTGOVWHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who do you think you will vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_INTGOVWHO

Universe

IF R DID NOT VOTE YET BUT INTENDS TO VOTE FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Do you prefer one of the candidates for Governor?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PREVOTE_GOVPREF

Universe

IF R DID NOT SAY THEY INTENDED TO VOTE FOR GOVERNOR:

Question

Who do you prefer?

Value Labels

-1. Inapplicable
1. Democratic Gubernatorial candidate
2. Republican Gubernatorial candidate
3. Indpendent Gubernatorial candidate
5. Another candidate {SPECIFY}

Survey Question(s)

PREVOTE_GOVPREFWHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who do you prefer?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PREVOTE_GOVPREFWHO

Universe

IF R DOES NOT INTEND TO VOTE BUT PREFERS A CANDIDATE FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Value Labels

-2. Missing - did not vote; no intent/preference given
-1. Inapplicable
10. Democratic candidate selected (vote)
11. Republican candidate selected (vote)
12. Other candidate selected (vote)
20. Democratic candidate selected (intent to vote)
21. Republican candidate selected (intent to vote)
22. Other candidate selected (intent to vote)
30. Democratic candidate selected (preference)
31. Republican candidate selected (preference)
32. Other candidate selected (preference)

Survey Question(s)

PREVOTE_PRESVTWHO, PREVOTE_INTPRESWHO, PREVOTE_PREFPRWHO, PAPI PRE Q7

Value Labels

Survey Question(s)

PREVOTE_HSVTWHO, PREVOTE_INTHSWHO,PREVOTE_HSPREFWHO

Value Labels

Survey Question(s)

PREVOTE_VTSENWHO, PREVOTE_INTSENWHO, PREVOTE_SENPREFWHO

Value Labels

Survey Question(s)

PREVOTE_VTGOVWHO, PREVOTE_INTGOVWHO, PREVOTE_GOVPREFWHO

Question

How likely is it that you will vote in the general election this November? [Extremely likely, very likely, moderately likely, slightly likely, or not likely at all / Not likely at all, slightly likely, moderately likely, very likely, or extremely likely]?

Value Labels

-1. Inapplicable
1. Extremely likely
2. Very likely
3. Moderately likely
4. Slightly likely
5. Not likely at all

Survey Question(s)

LIKELY_HOWLIKVT

Universe

IF R HAS NOT INDICATED DEFINITELY VOTED EARLY IN THE 2024 ELECTIONS:

Response Order

Forward/Reverse order

Question

How likely is it that you will vote in the general election this November?

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. I’ve already voted
2. Extremely likely
3. Very likely
4. Moderately likely
5. Slightly likely
6. Not likely at all

Survey Question(s)

PAPI PRE Q10

Value Labels

-9. Refused
-4. Error
1. I’ve already voted
2. Extremely likely
3. Very likely
4. Moderately likely
5. Slightly likely
6. Not likely at all

Survey Question(s)

PREVOTE_HOWVOTE, LIKELY_HOWLIKVT, PAPI PRE Q10

Question

Four years ago, in 2020, Joe Biden ran on the Democratic ticket against Donald Trump for the Republicans. We talk to many people who tell us they did not vote. And we talk to a few people who tell us they did vote, who really did not. We can tell they did not vote by checking with official government records.

What about you? If we check the official government voter records, will they show that you voted in the 2020 presidential election, or that you did not vote in that election?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes, voted
2. No, didn’t vote

Survey Question(s)

RETROVOTE_PRESVTLASTREV

Question

Which one did you vote for in 2020?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Joe Biden
2. Donald Trump
5. Another candidate {SPECIFY}

Survey Question(s)

RETROVOTE_PREVVTWHO

Universe

IF R SAYS VOTED FOR PRESIDENT IN 2020 PRESIDENTIAL ELECTION:

Question

Which one did you vote for in 2020?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

RETROVOTE_PREVVTWHO

Universe

IF R SAYS VOTED FOR PRESIDENT IN 2020 PRESIDENTIAL ELECTION:

Question

Four years ago, in 2020, Joe Biden ran against Donald Trump. Did you vote in that election four years ago?

Value Labels

-9. Refused
-1. Inapplicable
1. No, didn’t vote for president in 2020
2. Yes, for Donald Trump
3. Yes, for Joe Biden
4. Yes, for another candidate

Survey Question(s)

PAPI PRE Q11

Value Labels

-4. Error
-2. DK/RF in V241103, V241104, or V241105
1. No, didn’t vote for president in 2020
2. Yes, for Joe Biden
3. Yes, for Donald Trump
4. Yes, for another candidate

Survey Question(s)

RETROVOTE_PRESVTLASTREV, RETROVOTE_PREVVTWHO, PAPI PRE Q11

Question

Eight years ago, in 2016, Hillary Clinton ran on the Democratic ticket against Donald Trump for the Republicans. Do you remember for sure whether or not you voted in that election?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes, voted
2. No, didn’t vote

Survey Question(s)

RETROVOTE_PRESVT8YRAGO

Question

Which one did you vote for in 2016?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Hillary Clinton
2. Donald Trump
5. Another candidate {SPECIFY}

Survey Question(s)

RETROVOTE_PREVVT8YRWHO

Universe

IF R SAYS VOTED FOR PRESIDENT IN PRESIDENTIAL 2016 ELECTION:

Question

Which one did you vote for in 2016?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

RETROVOTE_PREVVT8YRWHO

Universe

IF R SAYS VOTED FOR PRESIDENT IN PRESIDENTIAL 2016 ELECTION:

Question

Is there anything in particular about Kamala Harris that might make you want to vote for her?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

CANDLIK_LIKEDPC

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

CANDLIK_LIKEWHATDPC

Universe

IF THERE IS SOMETHING THAT WOULD MAKE R VOTE FOR DEMOCRATIC PRES CAND:

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

Is there anything in particular about Kamala Harris that might make you want to vote against her?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

CANDLIK_DISLDPC

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

CANDLIK_DISLWHATDPC

Universe

IF THERE IS SOMETHING THAT WOULD MAKE R VOTE AGAINST DEMOCRATIC PRES CAND:

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

Is there anything in particular about Donald Trump that might make you want to vote for him?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

CANDLIK_LIKERPC

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

CANDLIK_LIKEWHATRPC

Universe

IF THERE IS SOMETHING THAT WOULD MAKE R VOTE FOR REPUBLICAN PRES CAND:

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

Is there anything in particular about Donald Trump that might make you want to vote against him?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

CANDLIK_DISLRPC

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

CANDLIK_DISLWHATRPC

Universe

IF THERE IS SOMETHING THAT WOULD MAKE R VOTE AGAINST REPUBLICAN PRES CAND:

Randomization

Order of Presidential candidates for the likes-dislikes set of questions.

Question

Do you feel things in this country are generally going in the right direction, or do you feel things have pretty seriously gotten off on the wrong track?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Right direction
2. Wrong track

Survey Question(s)

EMOTION_TRACK

Question

How hopeful do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTHOPE

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How afraid do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTAFRAID

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How outraged do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTRAGE

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How angry do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTANGRY

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How happy do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTHAPPY

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How worried do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTWORRY

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How proud do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTPROUD

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How irritated do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTIRRIT

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

How nervous do you feel about how things are going in the country? [Not at all, a little, somewhat, very, extremely / Extremely, very, somewhat, a little, not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Somewhat
4. Very
5. Extremely

Survey Question(s)

EMOTION_EMOTNERV

Randomization

Order of all items in EMOTION submodule after TRACK (EMOTHOPE, EMOTAFRAID, EMOTRAGE, EMOTANGRY, EMOTHAPPY, EMOTWORRY, EMOTPROUD, EMOTIRRIT, EMOTNERV)

Response Order

Forward/Reverse order

Question

Do you approve or disapprove of the way the U.S. Congress has been handling its job?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

CONGAPP_CONGJOB

Question

Do you [approve/disapprove] strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

CONGAPP_CONGJOBST

Universe

IF R APPROVES U.S. CONGRESS HANDLING ITS JOB /
IF R DISAPPROVES U.S. CONGRESS HANDLING ITS JOB:

Value Labels

-2. DK/RF in V241127 or V241128
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

CONGAPP_CONGJOB, CONGAPP_CONGJOBST

Question

Do you approve or disapprove of the way the Supreme Court has been handling its job?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

COURTAPP_COURTJOB

Question

Do you [approve/disapprove] strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

COURTAPP_COURTJOBSTR

Universe

IF R APPROVES SUPREME COURT HANDLING ITS JOB /
IF R DISAPPROVES SUPREME COURT HANDLING ITS JOB:

Question

Do you approve or disapprove of the way the Supreme Court has been handling its job?

Value Labels

-9. Refused
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PAPI PRE Q29

Value Labels

-2. DK/RF in V241130, V241131, or V241132
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

CONGAPP_CONGJOB, CONGAPP_CONGJOBST, PAPI PRE Q29

Question

Do you approve or disapprove of the way Joe Biden is handling his job as President?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESAPP_APPPRES

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESAPP_APPDISSTR

Universe

IF R APPROVES JOE BIDEN HANDLING JOB AS PRESIDENT /
IF R DISAPPROVES JOE BIDEN HANDLING JOB AS PRESIDENT:

Question

How strongly do you approve or disapprove of the way Joe Biden is handling his job as President?

Value Labels

-9. Refused
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PAPI PRE Q12

Value Labels

-2. DK/RF in V241134, V241135 or V241136
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESAPP_APPPRES, PRESAPP_APPDISSTR, PAPI PRE Q12

Question

Do you approve or disapprove of the way Kamala Harris is handling her job as
Vice President?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESAPP_APPVP

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not
strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESAPP_APPVPSTR

Universe

IF R APPROVES KAMALA HARRIS HANDLING JOB AS VICE PRESIDENT /
IF R DISAPPROVES KAMALA HARRIS HANDLING JOB AS VICE PRESIDENT:

Value Labels

-2. DK/RF in V241138 or V241139
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESAPP_APPVP, PRESAPP_APPVPSTR

Question

Do you approve or disapprove of the way Joe Biden is handling the economy?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESAPP_ECONPRES

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESAPP_ECONPRESST

Universe

IF R APPROVES JOE BIDEN HANDLING ECONOMY /
IF R DISAPPROVES JOE BIDEN HANDLING ECONOMY:

Value Labels

-2. DK/RF in V241141 or V241142
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESAPP_ECONPRES, PRESAPP_ECONPRESST

Question

Do you approve or disapprove of the way Joe Biden is handling relations with foreign countries?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESAPP_FRNPRES

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESAPP_FRNPRESST

Universe

IF R APPROVES JOE BIDEN HANDLING FOREIGN RELATIONS /
IF R DISAPPROVES JOE BIDEN HANDLING FOREIGN RELATIONS:

Value Labels

-2. DK/RF in V241144 or V241145
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESAPP_FRNPRES, PRESAPP_FRNPRESST

Question

Do you approve or disapprove of the way Joe Biden is handling abortion policy?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESAPP_ABRTPRES

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESAPP_ABRTPRESST

Universe

IF R APPROVES JOE BIDEN HANDLING ABORTION POLICY /
IF R DISAPPROVES JOE BIDEN HANDLING ABORTION POLICY:

Value Labels

-2. DK/RF in V241147 or V241148
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESAPP_ABRTPRES, PRESAPP_ABRTPRESST

Question

Do you approve or disapprove of the way Joe Biden is handling immigration?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESAPP_IMMIGPRES

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESAPP_IMMIGPRESST

Universe

IF R APPROVES JOE BIDEN HANDLING OF IMMIGRATION /
IF R DISAPPROVES JOE BIDEN HANDLING OF IMMIGRATION:

Value Labels

-2. DK/RF in V241150 or V241151
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESAPP_IMMIGPRES, PRESAPP_IMMIGPRESST

Question

Do you approve or disapprove of the way Joe Biden is handling crime?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

PRESAPP_CRIMEPRES

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PRESAPP_CRIMEPRESSTR

Universe

ASK IF R APPROVES JOE BIDEN HANDLING OF CRIME /
ASK IF R DISAPPROVES JOE BIDEN HANDLING OF CRIME:

Value Labels

-2. DK/RF in V241153 or V241154
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

PRESAPP_CRIMEPRES, PRESAPP_CRIMEPRESSTR

Question

(How would you rate:) Kamala Harris

Value Labels

-9. Refused
-8. Don’t know

Survey Question(s)

THERMPRE_THDPC, PAPI PRE Q15

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand + Biden thermometers (first three items of the THERMPRE submodule)

Question

(How would you rate:) Donald Trump

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THRPC, PAPI PRE Q14

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand + Biden thermometers (first three items of the THERMPRE submodule)

Question

(How would you rate:) Joe Biden

Value Labels

-9. Refused
-8. Don’t know

Survey Question(s)

THERMPRE_THBIDEN, PAPI PRE Q13

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand + Biden thermometers (first three items of the THERMPRE submodule)

Question

(How would you rate:) Robert F. Kennedy Jr.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THRRFK, PAPI PRE Q21

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize order of the following group: THRRFK, THSHAPIRO, THWHITMER, THKELLY, THCOOPER, THDVPC, THRVPC

Question

(How would you rate:) Josh Shapiro

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THSHAPIRO

Randomization

Randomize order of the following group: THRRFK, THSHAPIRO, THWHITMER, THKELLY, THCOOPER, THDVPC, THRVPC

Question

(How would you rate:) Gretchen Whitmer

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THWHITMER

Randomization

Randomize order of the following group: THRRFK, THSHAPIRO, THWHITMER, THKELLY, THCOOPER, THDVPC, THRVPC

Question

(How would you rate:) Mark Kelly

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THKELLY

Randomization

Randomize order of the following group: THRRFK, THSHAPIRO, THWHITMER, THKELLY, THCOOPER, THDVPC, THRVPC

Question

(How would you rate:) Roy Cooper

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THCOOPER

Randomization

Randomize order of the following group: THRRFK, THSHAPIRO, THWHITMER, THKELLY, THCOOPER, THDVPC, THRVPC

Question

(How would you rate:) J.D. Vance

Value Labels

-9. Refused
-8. Don’t know

Survey Question(s)

THERMPRE_THRVPC, PAPI PRE Q16

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize order of the following group: THRRFK, THSHAPIRO, THWHITMER, THKELLY, THCOOPER, THDVPC, THRVPC

Question

(How would you rate:) Tim Walz

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THDVPC, PAPI PRE Q17

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize order of the following group: THRRFK, THSHAPIRO, THWHITMER, THKELLY, THCOOPER, THDVPC, THRVPC

Question

(How would you rate:) the Democratic Party

Value Labels

-9. Refused
-8. Don’t know

Survey Question(s)

THERMPRE_THDPTY, PAPI PRE Q18

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of major party thermometers after all individual figure thermometers

Question

(How would you rate:) the Republican Party

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

THERMPRE_THRPTY, PAPI PRE Q19

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of major party thermometers after all individual figure thermometers

Question

How would you rate the MAGA movement?

Value Labels

-1. Inapplicable

Survey Question(s)

PAPI PRE Q20

Question

Is there anything in particular that you like about the Democratic party?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PTYLIK_LIKDP

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PTYLIK_LWHATDP

Universe

IF R SAYS THERE IS SOMETHING THAT R LIKES ABOUT DEMOCRATIC PARTY:

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

Is there anything in particular that you don’t like about the Democratic party?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PTYLIK_DISLDP

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PTYLIK_DWHATDP

Universe

IF R SAYS THERE IS SOMETHING THAT R DISLIKES ABOUT DEMOCRATIC PARTY:

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

Is there anything in particular that you like about the Republican party?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PTYLIK_LIKRP

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PTYLIK_LWHATRP

Universe

IF R SAYS THERE IS SOMETHING THAT R LIKES ABOUT REPUBLICAN PARTY:

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

Is there anything in particular that you don’t like about the Republican party?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

PTYLIK_DISLRP

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

(What is that?)

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PTYLIK_DWHATRP

Universe

IF R SAYS THERE IS SOMETHING THAT R DISLIKES ABOUT REPUBLICAN PARTY:

Randomization

Order of major parties for the likes-dislikes set of questions.

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-4. Error
1. Extremely liberal
2. Liberal
3. Slightly liberal
4. Moderate; middle of the road
5. Slightly conservative
6. Conservative
7. Extremely conservative
99. Haven’t thought much about this

Survey Question(s)

LIBCPRE_LCSELF, PAPI PRE Q44

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

If you had to choose, would you consider yourself a liberal or a conservative?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Liberal
2. Conservative

Survey Question(s)

LIBCPRE_LCCHOOSE

Universe

IF LIBERAL-CONSERVATIVE SELF-PLACEMENT IS MODERATE, DK, OR HAVEN’T THOUGHT:

Question

Where would you place Kamala Harris on this scale?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. Extremely liberal
2. Liberal
3. Slightly liberal
4. Moderate; middle of the road
5. Slightly conservative
6. Conservative
7. Extremely conservative
99. Haven’t thought much about this

Survey Question(s)

LIBCPRE_LCDPC, PAPI PRE Q44

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand liberal-conservative scale placements

Question

Where would you place Donald Trump on this scale?

Value Labels

Survey Question(s)

LIBCPRE_LCRPC, PAPI PRE Q44

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand liberal-conservative scale placements

Question

Where would you place the Democratic Party candidate in your district for the U.S. House of Representatives on this scale?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely liberal
2. Liberal
3. Slightly liberal
4. Moderate; middle of the road
5. Slightly conservative
6. Conservative
7. Extremely conservative
9. No such candidate

Survey Question(s)

LIBCPRE_LIBCHDC

Randomization

Order of House candidate liberal-conservative placements

Response Order

Randomize 2 major parties

Question

Where would you place the Republican Party candidate in your district for the U.S. House of Representatives on this scale?

Value Labels

Survey Question(s)

LIBCPRE_LIBCHRC

Randomization

Order of House candidate liberal-conservative placements

Response Order

Randomize 2 major parties

Question

Where would you place the Democratic Party on this scale?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely liberal
2. Liberal
3. Slightly liberal
4. Moderate; middle of the road
5. Slightly conservative
6. Conservative
7. Extremely conservative

Survey Question(s)

LIBCPRE_LCPTYD

Randomization

Order of party liberal-conservative scale placements

Question

Where would you place the Republican Party on this scale?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely liberal
2. Liberal
3. Slightly liberal
4. Moderate; middle of the road
5. Slightly conservative
6. Conservative
7. Extremely conservative

Survey Question(s)

LIBCPRE_LCPTYR

Randomization

Order of party liberal-conservative scale placements

Question

Do you approve or disapprove of Joe Biden dropping out of the presidential race?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

CAND_BIDENDROP

Question

Do you approve strongly or not strongly? / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

CAND_BIDENDROPSTR

Universe

IF R APPROVES BIDEN DROPPING OUT OF PRESIDENTIAL RACE /
IF R DISAPPROVES BIDEN DROPPING OUT OF PRESIDENTIAL RACE:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241185 or V241186
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

CAND_BIDENDROP, CAND_BIDENDROPSTR

Question

[Think about Kamala Harris. In your opinion, does the phrase ‘she provides strong leadership’ describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘provides strong leadership’? Does this phrase describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_DPCLEAD

Universe

IF TRAIT IS 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Kamala Harris. In your opinion, does the phrase ‘she really cares about people like you’ describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘really cares about people like you’? Does this phrase describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_DPCCARE

Universe

IF TRAIT IS 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Kamala Harris. In your opinion, does the phrase ‘she is knowledgeable’ describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘is knowledgeable’? Does this phrase describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_DPCKNOW

Universe

IF TRAIT IS 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Kamala Harris. In your opinion, does the phrase ‘she is honest’ describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘is honest’? Does this phrase describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_DPCHONST

Universe

IF TRAIT IS 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Kamala Harris. In your opinion, does the phrase ‘she is energetic’ describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘is energetic’? Does this phrase describe Kamala Harris [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_DPCENERG

Universe

IF TRAIT IS 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR DEMOCRATIC PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Donald Trump. In your opinion, does the phrase ‘he provides strong leadership’ describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘provides strong leadership’? Does this phrase describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_RPCLEAD

Universe

IF TRAIT IS 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Donald Trump. In your opinion, does the phrase ‘he really cares about people like you’ describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘really cares about people like you’? Does this phrase describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_RPCCARE

Universe

IF TRAIT IS 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Donald Trump. In your opinion, does the phrase ‘he is knowledgeable’ describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘is knowledgeable’? Does this phrase describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_RPCKNOW

Universe

IF TRAIT IS 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Donald Trump. In your opinion, does the phrase ‘he is honest’ describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘is honest’? Does this phrase describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_RPCHONST

Universe

IF TRAIT IS 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

[Think about Donald Trump. In your opinion, does the phrase ‘he is energetic’ describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]? / (What about) ‘is energetic’? Does this phrase describe Donald Trump [extremely well, very well, moderately well, slightly well, or not well at all/ not well at all, slightly well, moderately well, very well, or extremely well]?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

CTRAIT_RPCENERG

Universe

IF TRAIT IS 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE /
IF TRAIT IS NOT 1ST TRAIT FOR REPUBLICAN PRESIDENTIAL CANDIDATE:

Randomization

Order of Presidential cands for sets of traits;
order of traits administered for each candidate. Traits should be randomized in the same order for each candidate.

Response Order

Forward/Reverse order

Question

How much do you care who wins the presidential election this fall? [A great deal, a lot, a moderate amount, a little, or not at all / Not at all, a little, a moderate amount, a lot, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A great deal
2. A lot
3. A moderate amount
4. A little
5. Not at all

Survey Question(s)

PRESWIN_CAREWIN

Response Order

Forward/Reverse order

Question

Who do you think will be elected President in November?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Kamala Harris
2. Donald Trump
5. Other {SPECIFY} {VOL, FtF}

Survey Question(s)

PRESWIN_PRESPRED

Question

Who do you think will be elected President in November?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PRESWIN_PRESPRED

Question

Do you think the Presidential race will be close or will [Kamala Harris / Donald Trump / one candidate] win by quite a bit?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Will be close
2. Win by quite a bit

Survey Question(s)

PRESWIN_PRCLOSE

Universe

IF R THINKS DEMOCRATIC PRES CANDIDATE WILL WIN ELECTION /
IF R THINKS REPUBLICAN PRES CANDIDATE WILL WIN ELECTION /
IF R THINKS OTHER PRES CAND WILL WIN ELECTION /
IF R DOESN’T KNOW WHO WILL WIN PRESIDENTIAL ELECTION:

Question

What about here in [Respondent’s state for voting]? Which candidate for President do you think will carry this state?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Kamala Harris
2. Donald Trump
5. Other {SPECIFY} {VOL, FtF}

Survey Question(s)

PRESWIN_PRWINST

Question

What about here in [Respondent’s state for voting]? Which candidate for President do you think will carry this state?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PRESWIN_PRWINST

Question

Do you think the Presidential race will be close here in [Respondent’s state for voting] or will [Kamala Harris / Donald Trump / one candidate] win by quite a bit?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Will be close
2. Win by quite a bit

Survey Question(s)

PRESWIN_PRCLOSEST

Universe

Question

Different people feel differently about voting. For some, voting is a duty - they feel they should vote in every election no matter how they feel about the candidates and parties. For others voting is a choice - they feel free to vote or not to vote, depending on how they feel about the candidates and parties. For you personally, is voting mainly a duty, mainly a choice, or neither a duty nor a choice?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Mainly a duty
2. Mainly a choice
3. Neither a duty nor a choice

Survey Question(s)

PRESWIN_DUTYCHOICE

Question

How strongly do you feel that voting is a duty? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

PRESWIN_DUTYST

Universe

IF R CONSIDERS VOTING A DUTY:

Response Order

Forward/Reverse order

Question

How strongly do you feel that voting is a choice? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

PRESWIN_CHOICEST

Universe

IF R CONSIDERS VOTING A CHOICE:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241215, V241216, or V241217
-1. Inapplicable
1. Very strongly a duty
2. Moderately strongly a duty
3. A little strongly a duty
4. Neither a duty nor a choice
5. A little strongly a choice
6. Moderately strongly a choice
7. Very strongly a choice

Survey Question(s)

PRESWIN_DUTYCHOICE, PRESWIN_DUTYST, PRESWIN_CHOICEST

Question

Thinking about the 2024 general election, if your ballot has an option to vote for a straight-party ticket, that is, a single mark would allow you to vote for all of the candidates from a single party, would you most likely vote straight [Democrat / Republican], vote straight [Republican / Democrat], split your ballot between Democrats and Republicans depending on the office and the candidates, or something else?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Vote straight Democrat
2. Vote straight Republican
3. Split my ballot between Democrats and Republicans depending on the office and the candidates
4. Something else

Survey Question(s)

DIVGOV_SPLITTICKET

Response Order

Rand exc last

Question

Do you think it is better when one party controls both the presidency and Congress, better when control is split between the Democrats and Republicans, or doesn’t it matter?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Better when one party controls both
2. Better when control is split
3. It doesn’t matter

Survey Question(s)

DIVGOV_SPLITGOV

Question

Generally speaking, do you usually think of yourself as [a Democrat, a Republican / a Republican, a Democrat], an independent, or what?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. No preference {VOL, FtF}
1. Democrat
2. Republican
3. Independent
5. Other party {SPECIFY}

Survey Question(s)

PTYID_RPTYID

Randomization

Order of parties in question text and in response options 1 and 2 (randomized same, do not use candidateorder)

Response Order

Randomize 2 major parties

Question

Generally speaking, do you usually think of yourself as [a Democrat, a Republican / a Republican, a Democrat], an independent, or what?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

PTYID_RPTYID

Randomization

Order of parties in question text and in response options 1 and 2 (randomized same, do not use candidateorder)

Response Order

Randomize 2 major parties

Question

Would you call yourself a strong [Democrat / Republican] or a not very strong [Democrat / Republican]?

Value Labels

-9. Refused
-1. Inapplicable
1. Strong
2. Not very strong

Survey Question(s)

PTYID_STRPTYID

Universe

IF R CONSIDERS SELF A DEMOCRAT: /
IF R CONSIDERS SELF A REPUBLICAN :

Question

Do you think of yourself as closer to the Republican Party or to the Democratic Party?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Closer to Republican
2. Neither {VOL, FtF}
3. Closer to Democratic

Survey Question(s)

PTYID_LEANPTY

Universe

IF R’S PARTY IDENTIFICATION IS INDEPENDENT, NO PREFERENCE, OTHER, DK:

Question

Would you describe yourself as more of a supporter of the MAGA movement or more of a supporter of the Republican Party generally?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. MAGA movement
2. Republican Party generally

Survey Question(s)

PTYID_REPUBID

Universe

IF R CONSIDERS SELF A REPUBLICAN /
IF R CONSIDERS SELF CLOSER TO REPUBLICAN PARTY:

Question

If you had to choose, are you closer to the Democrats or the Republicans?
Or is there no difference at all between them?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. Closer to Democrats
2. Closer to Republicans
3. No difference at all

Survey Question(s)

PTYID_NEITHERID

Universe

IF MODE IS WEB /
IF R INDEPENDENT /
IF R DOES NOT LEAN REPUBLICAN OR DEMOCRAT:

Variable Note

This question should only have been asked of Web respondents; however, 52 FTF respondents received this question by mistake. Those cases have been recoded to -4 (Error)

Question

Here is a seven-point scale that describes the way many people think of themselves in terms of the major parties. Where would you place yourself on the following scale?

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Strong Democrat
2. Not very strong Democrat
3. independent leaning toward Democrat
4. independent
5. independent leaning toward Republican
6. Not very strong Republican
7. Strong Republican

Survey Question(s)

PAPI PRE Q23

Value Labels

-9. Refused
-8. Don’t know
-4. Error
1. Strong Democrat
2. Not very strong Democrat
3. Independent-Democrat
4. Independent
5. Independent-Republican
6. Not very strong Republican
7. Strong Republican

Survey Question(s)

PTYID_RPTYID, PTYID_STRPTYID, PTYID_LEANPTY, PTYID_NEITHERID, PAPI PRE Q23

Question

How important is being [a Democrat/a Republican/an Independent] to your identity? [Extremely important, very important, moderately important, a little important, or not at all important / Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

-9. Refused
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. A little important
5. Not at all important

Survey Question(s)

PTYID_PTYIDIMP

Universe

IF R CONSIDERS SELF A DEMOCRAT /
IF R CONSIDERS SELF A REPUBLICAN /
IF R CONSIDERS SELF AN INDEPENDENT:

Response Order

Forward/Reverse order

Question

How often can you trust the federal government in Washington to do what is right? [Always, most of the time, about half the time, some of the time, or never / Never, some of the time, about half the time, most of the time, or always]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Always
2. Most of the time
3. About half the time
4. Some of the time
5. Never

Survey Question(s)

TRUSTGOV_TRUSTGREV, PAPI PRE Q24

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How often can you trust the court system to do what is right? [Always, most of the time, about half the time, some of the time, or never / Never, some of the time, about half the time, most of the time, or always]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Always
2. Most of the time
3. About half the time
4. Some of the time
5. Never

Survey Question(s)

TRUSTGOV_TRUSTCOURT

Response Order

Forward/Reverse order

Question

Would you say the government is pretty much run by a few big interests looking out for themselves or that it is run for the benefit of all the people?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Run by a few big interests
2. For the benefit of all the people

Survey Question(s)

TRUSTGOV_BIGINTRST

Question

Do you think that people in government [waste a lot of the money we pay in taxes, waste some of it, or don’t waste very much of it / don’t waste very much of the money we pay in taxes, waste some of it, or waste a lot of it]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Waste a lot
2. Waste some
3. Don’t waste very much

Survey Question(s)

TRUSTGOV_WASTE

Response Order

Forward/Reverse order

Question

How many of the people running the government are corrupt? [All, most, about half, a few, or none? / None, a few, about half, most, or all?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. All
2. Most
3. About half
4. A few
5. None

Survey Question(s)

TRUSTGOV_CORRPT

Response Order

Forward/Reverse order

Question

Generally speaking, how often can you trust other people? [Always, most of the time, about half the time, some of the time, or never / Never, some of the time, about half the time, most of the time, or always]?

Value Labels

-9. Refused
-1. Inapplicable
1. Always
2. Most of the time
3. About half the time
4. Some of the time
5. Never

Survey Question(s)

TRUST_SOCTRUST, PAPI PRE Q25

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How much do you feel that having elections makes the government pay attention to what the people think? [A good deal, some, or not much / Not much, some, or a good deal]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A good deal
2. Some
3. Not much

Survey Question(s)

RESPONS_ELECTCARE

Response Order

Forward/Reverse order

Question

Which party do you think would do a better job of handling the nation’s economy?

[Democrats would do a much better job, Democrats would do a somewhat better job, not much difference between them, Republicans would do a somewhat better job, Republicans would do a much better job / Republicans would do a much better job, Republicans would do a somewhat better job, not much difference between them, Democrats would do a somewhat better job, Democrats would do a much better job]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Democrats would do a much better job
2. Democrats would do a somewhat better job
3. Not much difference between them
4. Republicans would do a somewhat better job
5. Republicans would do a much better job

Survey Question(s)

PTYPERF_PTYECON, PAPI PRE Q27

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Which party do you think would do a better job of handling immigration?

{READ IF NECESSARY} [Democrats would do a much better job, Democrats would do a somewhat better job, not much difference between them, Republicans would do a somewhat better job, Republicans would do a much better job / Republicans would do a much better job, Republicans would do a somewhat better job, not much difference between them, Democrats would do a somewhat better job, Democrats would do a much better job]

Value Labels

Survey Question(s)

PTYPERF_PTYIMMIG, PAPI PRE Q26

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Which party do you think would do a better job of handling the environment?

{READ IF NECESSARY} [Democrats would do a much better job, Democrats would do a somewhat better job, not much difference between them, Republicans would do a somewhat better job, Republicans would do a much better job / Republicans would do a much better job, Republicans would do a somewhat better job, not much difference between them, Democrats would do a somewhat better job, Democrats would do a much better job]

Value Labels

Survey Question(s)

PTYPERF_PTYENV

Response Order

Forward/Reverse order

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
1. Government should provide many fewer services
7. Government should provide many more services
99. Haven’t thought much about this

Survey Question(s)

SPSRVPR_SSSELF, PAPI PRE Q45

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Where would you place Kamala Harris on this issue?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. Government should provide many fewer services
7. Government should provide many more services
99. Haven’t thought much about this

Survey Question(s)

SPSRVPR_SSDPC, PAPI PRE Q45

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand services-spending scale placements

Question

Where would you place Donald Trump on this issue?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. Government should provide many fewer services
7. Government should provide many more services
99. Haven’t thought much about this

Survey Question(s)

SPSRVPR_SSRPC, PAPI PRE Q45

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand services-spending scale placements

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Greatly decrease defense spending
7. Greatly increase defense spending
99. Haven’t thought much about this

Survey Question(s)

DEFSPPR_DEFSPSELF

Question

Where would you place Kamala Harris on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Greatly decrease defense spending
7. Greatly increase defense spending

Survey Question(s)

DEFSPPR_DEFSPDPC

Randomization

Order of Presidential cand defense spending scale placements

Question

Where would you place Donald Trump on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Greatly decrease defense spending
7. Greatly increase defense spending

Survey Question(s)

DEFSPPR_DSPRERPC

Randomization

Order of Presidential cand defense spending scale placements

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Government insurance plan
7. Private insurance plan
99. Haven’t thought much about this

Survey Question(s)

INSPRE_INSSELF

Question

Where would you place Kamala Harris on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Government insurance plan
7. Private insurance plan

Survey Question(s)

INSPRE_INSDPC

Randomization

Order of Presidential cand govt-private insurance scale placements

Question

Where would you place Donald Trump on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Government insurance plan
7. Private insurance plan

Survey Question(s)

INSPRE_INSRPC

Randomization

Order of Presidential cand govt-private insurance scale placements

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Abortion should always be permitted without restrictions
7. Abortion should never be permitted
99. Haven’t thought much about this

Survey Question(s)

ABRTPRE_ABRTSELF

Question

On this scale from 1 to 7, where 1 means abortion should always be legal for any reason, and 7 means abortion should always be illegal with no exceptions, where would you place yourself?

Value Labels

-9. Refused
-1. Inapplicable
1. 1 Abortion always legal for any reason
7. Abortion always illegal with no exceptions

Survey Question(s)

PAPI PRE Q30

Question

Where would you place Kamala Harris on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Abortion should always be permitted without restrictions
7. Abortion should never be permitted

Survey Question(s)

ABRTPRE_ABRTDPC

Randomization

Randomize the order of ABRTDPC and ABRTRPC

Question

Where would you place Donald Trump on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Abortion should always be permitted without restrictions
7. Abortion should never be permitted

Survey Question(s)

ABRTPRE_ABRTRPC

Randomization

Randomize the order of ABRTDPC and ABRTRPC

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Government should see to jobs and standard of living
7. Government should let each person get ahead on own
99. Haven’t thought much about this

Survey Question(s)

GUARPR_GUARSELF

Question

Where would you place Kamala Harris on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Government should see to jobs and standard of living
7. Government should let each person get ahead on own

Survey Question(s)

GUARPR_GUARDPC

Randomization

Order of Presidential cand guaranteed job scale placements

Question

Where would you place Donald Trump on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Government should see to jobs and standard of living
7. Government should let each person get ahead on own

Survey Question(s)

GUARPR_GUARRPC

Randomization

Order of Presidential cand guaranteed job scale placements

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
1. Government should help blacks
7. Blacks should help themselves
99. Haven’t thought much about this

Survey Question(s)

AIDBPR_AIDBSELF, PAPI PRE Q46

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Where would you place Kamala Harris on this issue?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. Government should help blacks
7. Blacks should help themselves
99. Haven’t thought much about this

Survey Question(s)

AIDBPR_AIDBDPC, PAPI PRE Q46

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand aid to blacks scale placements

Question

Where would you place Donald Trump on this issue?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Government should help blacks
7. Blacks should help themselves
99. Haven’t thought much about this

Survey Question(s)

AIDBPR_AIDBRPC, PAPI PRE Q46

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Presidential cand aid to blacks scale placements

Question

Where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Tougher regulations on business needed to protect environment
7. Regulations to protect environment already too much a burden on business
99. Haven’t thought much about this

Survey Question(s)

ENVBUS_ENVBUSSELF

Question

Where would you place Kamala Harris on this scale?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Tougher regulations on business needed to protect environment
7. Regulations to protect environment already too much a burden on business

Survey Question(s)

ENVBUS_ENVBUSDPC

Randomization

Order of Presidential cand environment-jobs scale placements

Question

Where would you place Donald Trump on this scale?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Tougher regulations on business needed to protect environment
7. Regulations to protect environment already too much a burden on business

Survey Question(s)

ENVBUS_ENVBUSRPC

Randomization

Order of Presidential cand environment-jobs scale placements

Question

(What about) Social Security

(Should federal spending on Social Security be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSSS

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSSSSTR

Universe

IF R THINKS SPENDING ON SOCIAL SECURITY SHOULD BE INCREASED /
IF R THINKS SPENDING ON SOCIAL SECURITY SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241261 or V241262
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSSS, FEDSPEND_FSSSSTR

Question

(What about) Public schools

(Should federal spending on public schools be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSPUBS

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSPUBSSTR

Universe

IF R THINKS SPENDING ON PUBLIC SCHOOLS SHOULD BE INCREASED /
IF R THINKS SPENDING ON PUBLIC SCHOOLS SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241264 or V241265
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSPUBS, FEDSPEND_FSPUBSSTR

Question

(What about) Tightening border security to prevent illegal immigration

(Should federal spending on tightening border security to prevent illegal immigration be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSBRDR

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSBRDRSTR

Universe

IF R THINKS SPENDING ON BORDER SECURITY SHOULD BE INCREASED /
IF R THINKS SPENDING ON BORDER SECURITY SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241267 or V241268
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSBRDR, FEDSPEND_FSBRDRSTR

Question

(What about) Dealing with crime

(Should federal spending on dealing with crime be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSCRM

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSCRMSTR

Universe

IF R THINKS SPENDING ON DEALING WITH CRIME SHOULD BE INCREASED /
IF R THINKS SPENDING ON DEALING WITH CRIME SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241270 or V241271
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSCRM, FEDSPEND_FSCRMSTR

Question

(What about) Welfare programs

(Should federal spending on welfare programs be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSWELF

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSWELFSTR

Universe

IF R THINKS SPENDING ON WELFARE PROGRAMS SHOULD BE INCREASED /
IF R THINKS SPENDING ON WELFARE PROGRAMS SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241273 or V241274
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSWELF, FEDSPEND_FSWELFSTR

Question

(What about) Building and repairing highways

(Should federal spending on building and repairing highways be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSHIGH

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSHIGHSTR

Universe

IF R THINKS SPENDING ON HIGHWAYS SHOULD BE INCREASED /
IF R THINKS SPENDING ON HIGHWAYS SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241276 or V241277
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSHIGH, FEDSPEND_FSHIGHSTR

Question

(What about) Aid to the poor

(Should federal spending on aid to the poor be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSPR

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSPRSTR

Universe

IF R THINKS SPENDING ON AID TO THE POOR SHOULD BE INCREASED /
IF R THINKS SPENDING ON AID TO THE POOR SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241279 or V241280
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSPR, FEDSPEND_FSPRSTR

Question

(What about) Protecting the environment

(Should federal spending on protecting the environment be increased, decreased, or kept the same?)

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Kept the same

Survey Question(s)

FEDSPEND_FSENV

Randomization

Randomize order of federal spending items

Question

Should it be [increased / decreased] a lot or a little?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

FEDSPEND_FSENVSTR

Universe

IF R THINKS SPENDING ON PROTECTING THE ENVIRONMENT SHOULD BE INCREASED /
IF R THINKS SPENDING ON PROTECTING THE ENVIRONMENT SHOULD BE DECREASED:

Value Labels

-2. DK/RF in V241282 or V241283
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Kept the same
4. Decreased a little
5. Decreased a lot

Survey Question(s)

FEDSPEND_FSENV, FEDSPEND_FSENVSTR

Question

Do you approve, disapprove, or neither approve nor disapprove of how most colleges and universities are run these days?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove
3. Neither approve nor disapprove

Survey Question(s)

UNI_UNIRUN

Question

How strongly do you feel that way? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

UNI_UNIRUNSTR

Universe

IF R APPROVES HOW COLLEGES ARE RUN /
IF R DISAPPROVES HOW COLLEGES ARE RUN:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241285 or V241286
-1. Inapplicable
1. Approve very strongly
2. Approve somewhat strongly
3. Approve not very strongly
4. Neither approve nor disapprove
5. Disapprove not very strongly
6. Disapprove somewhat strongly
7. Disapprove strongly

Survey Question(s)

UNI_UNIRUN, UNI_UNIRUNSTR

Question

Do you favor, oppose, or neither favor nor oppose Diversity, Equity, and Inclusion (DEI) policies on college campuses that influence admission, hiring, and promotion?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

UNI_DEI

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

UNI_DEISTR

Universe

IF R FAVORS DEI POLICIES /
IF R OPPOSES DEI POLICIES:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241288 or V241289
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

UNI_DEI, UNI_DEISTR

Question

Now thinking about the economy in the country as a whole, would you say that over the past year the nation’s economy has gotten better, stayed about the same, or gotten worse?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Gotten better
2. Stayed about the same
3. Gotten worse

Survey Question(s)

ECON_ECPAST

Question

[Much better or somewhat better? / Much worse or somewhat worse?]

Value Labels

-9. Refused
-1. Inapplicable
1. Much
2. Somewhat

Survey Question(s)

ECON_ECPASTAMT

Universe

IF R THINKS THE ECONOMY HAS GOTTEN BETTER IN THE PAST YEAR /
IF R THINKS THE ECONOMY HAS GOTTEN WORSE IN THE PAST YEAR:

Question

Now thinking about the economy in the country as a whole, would you say that over the past year the nation’s economy has gotten better, stayed about the same, or gotten worse?

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Gotten much better
2. Gotten somewhat better
3. Stayed about the same
4. Gotten somewhat worse
5. Gotten much worse

Survey Question(s)

PAPI PRE Q28

Value Labels

-4. Error
-2. DK/RF in V241291, V241292, or V241293
1. Gotten much better
2. Gotten somewhat better
3. Stayed about the same
4. Gotten somewhat worse
5. Gotten much worse

Survey Question(s)

ECON_ECPAST, ECON_ECPASTAMT, PAPI PRE Q28

Question

What about the next 12 months? Do you expect the economy, in the country as a whole, to get better, stay about the same, or get worse?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Get better
2. Stay about the same
3. Get worse

Survey Question(s)

ECON_ECNEXT

Question

[Much better or somewhat better / Much worse or somewhat worse]?

Value Labels

-9. Refused
-1. Inapplicable
1. Much
2. Somewhat

Survey Question(s)

ECON_ECNEXTAMT

Universe

IF R THINKS ECONOMY WILL BE BETTER IN NEXT 12 MONTHS /
IF R THINKS ECONOMY WILL BE WORSE IN NEXT 12 MONTHS:

Value Labels

-2. DK/RF in V241295 or V241296
-1. Inapplicable
1. Get much better
2. Get somewhat better
3. Stayed about the same
4. Get somewhat worse
5. Get much worse

Survey Question(s)

ECON_ECNEXT, ECON_ECNEXTAMT

Question

Would you say that over the past year, the level of unemployment in the country has gotten better, stayed about the same, or gotten worse?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Better
2. About the same
3. Worse

Survey Question(s)

ECON_UNPAST

Question

[Would you say much better or somewhat better / Would you say much worse or somewhat worse]?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. Much
2. Somewhat

Survey Question(s)

ECON_UNAMT

Universe

IF R SAYS UNEMPLOYMENT HAS GOTTEN BETTER /
IF R SAYS UNEMPLOYMENT HAS GOTTEN WORSE:

Value Labels

-2. DK/RF in V241298 or V241299
-1. Inapplicable
1. Much better
2. Somewhat better
3. About the same
4. Somewhat worse
5. Much worse

Survey Question(s)

ECON_UNPAST, ECON_UNAMT

Question

How about people out of work during the coming 12 months – do you think that there will be more unemployment than now, about the same, or less?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. More
2. About the same
3. Less

Survey Question(s)

ECON_UNNEXT

Question

There has been some discussion about abortion during recent years. Which one of the opinions on this page best agrees with your view? You can just tell me the number of the opinion you choose.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. By law, abortion should never be permitted
2. The law should permit abortion only in case of rape, incest, or when the woman’s life is in danger
3. The law should permit abortion other than for rape/incest/danger to woman but only after need clearly established
4. By law, a woman should always be able to obtain an abortion as a matter of personal choice
5. Other {SPECIFY}

Survey Question(s)

ABORTPRE_ABSELFSTD

Question

There has been some discussion about abortion during recent years. Which one of the opinions on this page best agrees with your view? You can just tell me the number of the opinion you choose.

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

ABORTPRE_ABSELFSTD

Question

How important is this issue to you personally? [Not at all important, not too important, somewhat important, very important, or extremely important / extremely important, very important, somewhat important, not too important, not at all important]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all important
2. Not too important
3. Somewhat important
4. Very important
5. Extremely important

Survey Question(s)

ABORTPRE_ABSELFIMP

Response Order

Forward/Reverse order

Question

Where would you place Kamala Harris (on abortion)?

Value Labels

Survey Question(s)

ABORTPRE_ABDPCSTD

Randomization

Order of Pres cand abortion placements

Question

Where would you place Donald Trump (on abortion)?

Value Labels

Survey Question(s)

ABORTPRE_ABRPCSTD

Randomization

Order of Pres cand abortion placements

Question

Do you favor or oppose the death penalty for persons convicted of murder?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose

Survey Question(s)

PENALTY_FAVDPEN

Question

Do you [favor / oppose] the death penalty for persons convicted of murder strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

PENALTY_DPENSTR

Universe

IF R FAVORS DEATH PENALTY FOR PERSONS CONVICTED OF MURDER /
IF R OPPOSES DEATH PENALTY FOR PERSONS CONVICTED OF MURDER:

Value Labels

-2. DK/RF in V241306 or V241307
-1. Inapplicable
1. Favor strongly
2. Favor not strongly
3. Oppose not strongly
4. Oppose strongly

Survey Question(s)

PENALTY_FAVDPEN, PENALTY_DPENSTR

Question

Turning to some questions about America’s role in the world: During the past year, would you say that the United States’ position in the world has grown [weaker, stayed about the same, or has it grown stronger / stronger, stayed about the same, or has it grown weaker]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Weaker
2. Stayed about the same
3. Stronger

Survey Question(s)

USWORLD_USSTR

Response Order

Forward/Reverse order

Question

Do you agree or disagree with this statement: ‘This country would be better off if we just stayed home and did not concern ourselves with problems in other parts of the world.’

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Agree
2. Disagree

Survey Question(s)

USWORLD_USISOL

Question

Do you agree strongly or agree somewhat with this statement? / Do you disagree strongly or disagree somewhat with this statement?

Value Labels

-9. Refused
-1. Inapplicable
1. Strongly
2. Somewhat

Survey Question(s)

USWORLD_USISOLSTR

Universe

IF R AGREES COUNTRY BETTER IF WE STAYED HOME /
IF R DISAGREES COUNTRY BETTER IF WE STAYED HOME:

Value Labels

-2. DK/RF in V241309 or V241310
-1. Applicable
1. Agree strongly
2. Agree somewhat
3. Disagree somewhat
4. Disagree strongly

Survey Question(s)

USWORLD_USISOL, USWORLD_USISOLSTR

Question

How willing should the United States be to use military force to solve international problems? [Extremely willing, very willing, moderately willing, a little willing, or not at all willing / Not at all willing, a little willing, moderately willing, very willing, or extremely willing]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely willing
2. Very willing
3. Moderately willing
4. A little willing
5. Not at all willing

Survey Question(s)

USWORLD_MILFORCE

Response Order

Forward/Reverse order

Question

In the November 2024 general election, how accurately do you think the votes will be counted? [Not at all accurately, a little accurately, moderately accurately, very accurately, or completely accurately / Completely accurately, very accurately, moderately accurately, a little accurately, or not at all accurately]?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. Not at all accurately
2. A little accurately
3. Moderately accurately
4. Very accurately
5. Completely accurately

Survey Question(s)

ELECTINTPRE_VOTECOUNT, PAPI PRE Q22

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How much do you trust the officials who oversee elections where you live? [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. A moderate amount
4. A lot
5. A great deal

Survey Question(s)

ELECTINTPRE_VOTETRUST

Response Order

Forward/Reverse order

Question

How often are people who are eligible to vote denied the right to vote? [Never, rarely, occasionally, fairly often, or very often / Very often, fairly often, occasionally, rarely, or never]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Never
2. Rarely
3. Occasionally
4. Fairly often
5. Very often

Survey Question(s)

ELECTINTPRE_VOTESTOP

Response Order

Forward/Reverse order

Question

Do you favor, oppose, or neither favor nor oppose requiring all people to show a government issued photo ID when they vote?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

ELECTINTPRE_VOTESHOWID

Question

Do you [favor / oppose] that [a great deal, moderately, or a little / a little, moderately, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A great deal
2. Moderately
3. A little

Survey Question(s)

ELECTINTPRE_VOTESHOWIDSTR

Universe

IF R FAVORS SHOWING GOVT PHOTO ID /
IF R OPPOSES SHOWING GOVT PHOTO ID:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241317 or V241318
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

ELECTINTPRE_VOTESHOWID, ELECTINTPRE_VOTESHOWIDSTR

Question

Do you favor, oppose, or neither favor nor oppose allowing convicted felons to vote once they complete their sentence?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

ELECTINTPRE_VOTEFELON

Question

Do you [favor / oppose] that [a great deal, moderately, or a little / a little, moderately, or a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. Moderately
3. A little

Survey Question(s)

ELECTINTPRE_VOTEFELONSTR

Universe

IF R FAVORS ALLOWING FELONS TO VOTE /
IF R OPPOSES ALLOWING FELONS TO VOTE:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241319 or V241320
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

ELECTINTPRE_VOTEFELON, ELECTINTPRE_VOTEFELONSTR

Question

In your state, are people required to show identification when voting? Would you say yes, no, or are you unsure?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No
3. Unsure

Survey Question(s)

ELECTINTPRE_VOTEIDSTATE

Question

For the next few items, we would like to know how important you think each one is to the United States maintaining a strong democracy.

First, how important is it that news organizations are free to criticize political leaders? [Not important at all, a little important, moderately important, very important, or extremely important / Extremely important, very important, moderately important, a little important, not important at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not important at all
2. A little important
3. Moderately important
4. Very important
5. Extremely important

Survey Question(s)

DEMNORMS_DEMCRIT

Response Order

Forward/Reverse order

Question

How important is it that the executive, legislative, and judicial branches of government keep one another from having too much power? [Not important at all, a little important, moderately important, very important, or extremely important / Extremely important, very important, moderately important, a little important, not important at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not important at all
2. A little important
3. Moderately important
4. Very important
5. Extremely important

Survey Question(s)

DEMNORMS_DEMBRANCH

Response Order

Forward/Reverse order

Question

How important is it that elected officials face serious consequences if they engage in misconduct? [Not important at all, a little important, moderately important, very important, or extremely important / Extremely important, very important, moderately important, a little important, not important at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not important at all
2. A little important
3. Moderately important
4. Very important
5. Extremely important

Survey Question(s)

DEMNORMS_DEMCONSEQ

Response Order

Forward/Reverse order

Question

How important is it that people agree on basic facts even if they disagree politically? [Not important at all, a little important, moderately important, very important, or extremely important / Extremely important, very important, moderately important, a little important, not important at all]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not important at all
2. A little important
3. Moderately important
4. Very important
5. Extremely important

Survey Question(s)

DEMNORMS_DEMFACTS

Response Order

Forward/Reverse order

Question

Would it be helpful, harmful, or neither helpful nor harmful if U.S. presidents could work on the country’s problems without paying attention to what Congress and the courts say?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Helpful
2. Harmful
3. Neither helpful nor harmful

Survey Question(s)

DEMNORMS_STRPRES

Question

How [helpful / harmful]? [Extremely, moderately, or a little / A little, moderately, or extremely]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely
2. Moderately
3. A little

Survey Question(s)

DEMNORMS_STRPRESSTR

Universe

IF R SAID HELPFUL /
IF R SAID HARMFUL:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241328 or V241329
-1. Inapplicable
1. Extremely helpful
2. Moderately helpful
3. A little helpful
4. Neither helpful nor harmful
5. A little harmful
6. Moderately harmful
7. Extremely harmful

Survey Question(s)

DEMNORMS_STRPRES, DEMNORMS_STRPRESSTR

Question

Do you favor, oppose, or neither favor nor oppose elected officials restricting journalists’ access to information about government decision-making?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

DEMNORMS_JOURNACCESS

Question

Do you [favor / oppose] that [a great deal, moderately, or a little / a little, moderately, or a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. Moderately
3. A little

Survey Question(s)

DEMNORMS_JOURNACCESSSTR

Universe

IF R FAVORS RESTRICTING JOURNALIST ACCESS /
IF R OPPOSES RESTRICTING JOURNALIST ACCESS:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241331 or V241332
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

DEMNORMS_JOURNACCESS, DEMNORMS_JOURNACCESSSTR

Question

How concerned are you that some people in the government today might want to undermine the news media’s ability to serve as a check on governmental power? [Not at all concerned, a little concerned, moderately concerned, very concerned, or extremely concerned / Extremely concerned, very concerned, moderately concerned, a little concerned, or not at all concerned]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all concerned
2. A little concerned
3. Moderately concerned
4. Very concerned
5. Extremely concerned

Survey Question(s)

DEMNORMS_MEDIACHECK

Response Order

Forward/Reverse order

Question

In general, how much trust and confidence do you have in the news media when it comes to reporting the news fully, accurately, and fairly? [None, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or none]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. None
2. A little
3. A moderate amount
4. A lot
5. A great deal

Survey Question(s)

DEMNORMS_MEDIATRUST

Response Order

Forward/Reverse order

Question

Would you prefer a government official who compromises to get things done, or who sticks to their principles no matter what?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Compromises to get things done
2. Sticks to their principles no matter what

Survey Question(s)

COMPROMISE_PREFCOMP

Question

How strongly do you feel this way? [Very strongly, moderately strongly, or slightly strongly / slightly strongly, moderately strongly, or very strongly]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Very strongly
2. Moderately strongly
3. Slightly strongly

Survey Question(s)

COMPROMISE_PREFCOMPSTR

Universe

IF R PREFERS GOVERNMENT OFFICIALS TO COMPROMISE TO GET THINGS DONE /
IF R PREFERS GOVERNMENT OFFICIALS TO STICK TO THEIR PRINCIPALS:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241336 or V241337
-1. Inapplicable
1. Prefers gov official who compromises very strongly
2. Prefers gov official who compromises moderately strongly
3. Prefers gov official who compromises slightly strongly
4. Prefers gov official who sticks to principles slightly strongly
5. Prefers gov official who sticks to principles moderately strongly
6. Prefers gov official who sticks to principles very strongly

Survey Question(s)

COMPROMISE_PREFCOMP, COMPROMISE_PREFCOMPSTR

Question

How likely would the following be to keep you from voting for a candidate you otherwise liked?

The candidate has been convicted of a felony

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely likely
2. Very likely
3. Moderately likely
4. Slightly likely
5. Not likely at all

Survey Question(s)

DISQUAL_FELON

Randomization

Randomize items in DISQUAL submodule after INTRO (FELON, DOCS, SEXHAR)

Response Order

Forward/Reverse order

Question

How likely would the following be to keep you from voting for a candidate you otherwise liked?

The candidate mishandled top secret documents

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely likely
2. Very likely
3. Moderately likely
4. Slightly likely
5. Not likely at all

Survey Question(s)

DISQUAL_DOCS

Randomization

Randomize items in DISQUAL submodule after INTRO (FELON, DOCS, SEXHAR)

Question

How likely would the following be to keep you from voting for a candidate you otherwise liked?

Evidence of sexual harassment by the candidate

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely likely
2. Very likely
3. Moderately likely
4. Slightly likely
5. Not likely at all

Survey Question(s)

DISQUAL_SEXHAR

Randomization

Randomize items in DISQUAL submodule after INTRO (FELON, DOCS, SEXHAR)

Question

Has corruption in government increased, decreased, or stayed the same since Joe Biden became president?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Increased
2. Decreased
3. Stayed the same

Survey Question(s)

BIDENIMPEACH_CORRUPTJB

Question

Has corruption [increased / decreased] [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

BIDENIMPEACH_CORRUPTJBSTR

Universe

IF R SAYS CORRUPTION INCREASED /
IF R SAYS CORRUPTION DECREASED:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241341 or V241342
-1. Inapplicable
1. Increased a great deal
2. Increased a moderate amount
3. Increased a little
4. Stayed the same
5. Decreased a little
6. Decreased a moderate amount
7. Decreased a great deal

Survey Question(s)

BIDENIMPEACH_CORRUPTJB, BIDENIMPEACH_CORRUPTJBSTR

Question

Do you think the Manhattan jury that found Donald Trump guilty of felonies made the right decision or the wrong decision?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Right decision
2. Wrong decision

Survey Question(s)

TRUMP_MHTN

Question

How strongly do you feel that way? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-9. Refused
-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

TRUMP_MHTNSTR

Universe

IF R THINKS MANHATTAN JURY DECISION WAS RIGHT DECISION /
IF R THINKS MANHATTAN JURY DECISION WAS WRONG DECISION:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241345 or V241346
-1. Inapplicable
1. Thinks very strongly Manhattan jury made right decision
2. Thinks somewhat strongly Manhattan jury made right decision
3. Thinks not strongly Manhattan jury made right decision
4. Thinks not strongly Manhattan jury made wrong decision
5. Thinks somewhat strongly Manhattan jury made wrong decision
6. Thinks very strongly Manhattan jury made wrong decision

Survey Question(s)

TRUMP_MHTN, TRUMP_MHTNSTR

Question

Do you approve or disapprove of the Supreme Court decision that a former president is immune from criminal prosecution for official acts performed as president?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

TRUMP_SCIMMUNE

Question

How strongly do you feel that way? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-9. Refused
-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

TRUMP_SCIMMUNESTR

Universe

IF R APPROVES SUPREME COURT DECISION /
IF R DISAPPROVES SUPREME COURT DECISION:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241348 or V241349
-1. Inapplicable
1. Approve very strongly
2. Approve somewhat strongly
3. Approve not strongly
4. Disapprove not strongly
5. Disapprove somewhat strongly
6. Disapprove very strongly

Survey Question(s)

TRUMP_SCIMMUNE, TRUMP_SCIMMUNESTR

Question

Have the courts treated Donald Trump fairly or unfairly?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Fairly
2. Unfairly

Survey Question(s)

TRUMP_COURTFAIR

Question

How strongly do you feel that way? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly.]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

TRUMP_COURTFAIRSTR

Universe

IF R THINKS COURTS HAVE TREATED TRUMP FAIRLY /
IF R THINKS COURTS HAVE TREATED TRUMP UNFAIRLY:

Response Order

Forward/Reverse order

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Value Labels

-2. DK/RF in V241351 or V241352
-1. Inapplicable
1. Believes very strongly courts have treated Trump fairly
2. Believes somewhat strongly courts have treated Trump fairly
3. Believes not strongly courts have treated Trump fairly
4. Believes not strongly courts have treated Trump unfairly
5. Believes somewhat strongly courts have treated Trump unfairly
6. Believes very strongly courts have treated Trump unfairly

Survey Question(s)

TRUMP_COURTFAIR, TRUMP_COURTFAIRSTR

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

Do you think the difference in incomes between rich people and poor people in the United States today is larger, smaller, or about the same as it was 20 years ago?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Larger
2. Smaller
3. About the same

Survey Question(s)

INEQ_INCGAP

Question

Would you say the difference in incomes is much larger or somewhat larger?

Value Labels

-9. Refused
-1. Inapplicable
1. Much
2. Somewhat

Survey Question(s)

INEQ_GAPMORE

Universe

IF INCOME GAP TODAY IS LARGER THAN IT WAS 20 YEARS AGO:

Question

Would you say the difference in incomes is much smaller or somewhat smaller?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Much
2. Somewhat

Survey Question(s)

INEQ_GAPLESS

Universe

IF INCOME GAP TODAY IS SMALLER THAN IT WAS 20 YEARS AGO:

Value Labels

-2. DK/RF in V241360, V241361, or V241362
-1. Inapplicable
1. Much larger
2. Somewhat larger
3. About the same
4. Somewhat smaller
5. Much smaller

Survey Question(s)

INEQ_INCGAP, INEQ_GAPMORE, INEQ_GAPLESS

Question

Do you think the federal government should be doing more about rising temperatures, should be doing less, or is it currently doing the right amount?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Should be doing more
2. Should be doing less
3. Is currently doing the right amount

Survey Question(s)

ENVIR_WARMDO

Question

Should it be doing a great deal [more/less], a moderate amount [more/less], or a little [more/less]? / Should it be doing a little [more/less], a moderate amount [more/less], or a great deal [more/less]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

ENVIR_WARMDOAMT

Universe

IF R SAYS GOVERNMENT SHOULD DO MORE ABOUT RISING TEMPERATURES /
IF R SAYS GOVERNMENT SHOULD DO LESS ABOUT RISING TEMPERATURES:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241364 or V241365
-1. Inapplicable
1. Should be doing a great deal more
2. Should be doing a moderate amount more
3. Should be doing a little more
4. Currently doing the right amount
5. Should be doing a little less
6. Should be doing a moderate amount less
7. Should be doing a great deal less

Survey Question(s)

ENVIR_WARMDO, ENVIR_WARMDOAMT

Question

Do you favor, oppose, or neither favor nor oppose requiring employers to offer paid leave to parents of new children?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

GENDPOL_PARLEAVE

Question

Do you favor that a great deal, a moderate amount, or a little ? / Do you oppose that a great deal, a moderate amount, or a little?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

GENDPOL_PARLEAVESTR

Universe

IF R FAVORS REQUIRING EMPLOYERS TO OFFER PAID LEAVE FOR NEW CHILDREN /
IF R OPPOSES REQUIRING EMPLOYERS TO OFFER PAID LEAVE FOR NEW CHILDREN :

Value Labels

-2. DK/RF in V241367 or V241368
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

GENDPOL_PARLEAVE, GENDPOL_PARLEAVESTR

Question

Do you favor, oppose, or neither favor nor oppose allowing transgender people to use public bathrooms that match the gender they identify with?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

TRANSPOLICY_RESTRM

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

TRANSPOLICY_RESTRMSTR

Universe

IF R FAVORS ALLOWING TRANSGENDER PEOPLE TO USE BATHROOM THAT MATCHES THE GENDER THEY IDENIFY WITH /
IF R OPPOSES ALLOWING TRANSGENDER PEOPLE TO USE BATHROOM THAT MATCHES THE GENDER THEY IDENTIFY WITH:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241370 or V241371
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

TRANSPOLICY_RESTRM, TRANSPOLICY_RESTRMSTR

Question

Several states have considered laws that would ban transgender girls from participating in K-12 girls’ sports. Do you favor, oppose, or neither favor nor oppose such a law?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

TRANSPOLICY_TRANSPRT

Variable Note

PAPI respondents received this question in the post-election interview. A pre-post summary variable has been created to summarize the responses from all modes.

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little/ a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

TRANSPOLICY_TRANSPRTSTR

Universe

IF R FAVORS BAN /
IF R OPPOSES BAN:

Response Order

Forward/Reverse order

Variable Note

PAPI respondents received this question in the post-election interview. A pre-post summary variable has been created to summarize the responses from all modes.

Value Labels

-2. DK/RF in V241373 or V241374
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

TRANSPOLICY_TRANSPRT, TRANSPOLICY_TRANSPRTSTR

Question

Do you favor or oppose laws to protect gays and lesbians against job discrimination?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose

Survey Question(s)

GAYRT_GDISCREV

Question

[Do you favor such laws strongly or not strongly? / Do you oppose such laws strongly or not strongly?]

Value Labels

-9. Refused
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

GAYRT_GDISCSTREV

Universe

IF R FAVORS PROTECTING GAYS AND LESBIANS AGAINST JOB DISCRIMINATION/
IF R OPPOSES PROTECTING GAYS AND LESBIANS AGAINST JOB DISCRIMINATION:

Value Labels

-2. DK/RF in V241376 or V241377
-1. Inapplicable
1. Favor strongly
2. Favor not strongly
3. Oppose not strongly
4. Oppose strongly

Survey Question(s)

GAYRT_GDISCREV, GAYRT_GDISCSTREV

Question

Do you think gay or lesbian couples should be legally permitted to adopt children?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

GAYRT_GAYADOPT

Question

How strongly do you feel that way? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

GAYRT_GAYADOPTSTR

Universe

IF R SAYS YES GAY OR LESBIAN COUPLES SHOULD BE LEGALLY PERMITTED TO ADOPT CHILDREN /
IF R SAYS NO GAY OR LESBIAN COUPLES SHOULD NOT BE LEGALLY PERMITTED TO ADOPT CHILDREN:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241379 or V241380
-1. Inapplicable
1. Feels very strongly gay/lesbian couples should be permitted to adopt
2. Feels somewhat strongly gay/lesbian couples should be permitted to adopt
3. Feels not strongly gay/lesbian couples should be permitted to adopt
4. Feels not strongly gay/lesbian couples should not be permitted to adopt
5. Feels somewhat strongly gay/lesbian couples should not be permitted to adopt
6. Feels very strongly gay/lesbian couples should not be permitted to adopt

Survey Question(s)

GAYRT_GAYADOPT, GAYRT_GAYADOPTSTR

Question

Which comes closest to your view? You can just tell me the number of your choice.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Gay and lesbian couples should be allowed to legally marry
2. Gay and lesbian couples should be allowed to form civil unions but not legally marry
3. There should be no legal recognition of gay or lesbian couples’ relationship

Survey Question(s)

GAYRT_GAYMARR

Universe

IF R SELECTED FOR VERSION 1A OF VERSION 1A / VERSION 1B SPLICE:

Question

Do you favor or oppose, or neither favor nor oppose the right of gay and lesbian couples to legally marry?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

GAYRT_GAYMARR2

Universe

IF R SELECTED FOR VERSION 1B OF VERSION 1A / VERSION 1B SPLICE:

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

GAYRT_GAYMARR2STR

Universe

IF R SELECTED FOR VERSION 1B OF VERSION 1A / VERSION 1B SPLICE /
IF R FAVORS THE RIGHT OF GAY/LESBIAN COUPLES TO LEGALLY MARRY /
IF R OPPOSES THE RIGHT OF GAY/LESBIAN COUPLES TO LEGALLY MARRY:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241383 or V241384
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

GAYRT_GAYMARR2, GAYRT_GAYMARR2STR

Question

Which comes closest to your view about what government policy should be toward unauthorized immigrants now living in the United States? You can just tell me the number of your choice.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Make all unauthorized immigrants felons and send them back to their home country
2. Have guest worker program that allows unauthorized immigrants to remain in the US to work but only for a limited amount of time
3. Allow unauthorized immigrants to remain in US & qualify for citizenship if they meet certain requirements
4. Allow unauthorized immigrants to remain in US & qualify for citizenship without penalties

Survey Question(s)

IMMIG_IMMPOL

Question

Some people have proposed that the U.S. Constitution should be changed so that the children of unauthorized immigrants do not automatically get citizenship if they are born in this country. Do you favor, oppose, or neither favor nor oppose this proposal?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

IMMIG_BRTCITRT

Question

Do you favor that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]? / Do you oppose that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

IMMIG_BIRTHRTSTR

Universe

IF R FAVORS CHANGING CONSTITUTION - US-BORN CHILDREN OF OF ILLEGAL IMMIGRANTS /
IF R OPPOSES CHANGING CONSTITUTION - US-BORN CHILDREN OF OF ILLEGAL IMMIGRANTS:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241387 or V241388
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

IMMIG_BRTCITRT, IMMIG_BIRTHRTSTR

Question

What should happen to immigrants who were brought to the U.S. illegally as children and have lived here for at least 10 years and graduated high school here? Should they be sent back where they came from, or should they be allowed to live and work in the United States?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Should be sent back where they came from
2. Should be allowed to live and work in the US

Survey Question(s)

IMMIG_CHILD

Question

Do you favor that [a great deal, a moderate amount, or a little / a little, a moderate amount, a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

IMMIG_CHILDSTR

Universe

IF R R OPINION ON ILLEGAL IMMIGRANT CHILDREN RAISED IN U.S. IS NOT DK/RF:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241390 or V241391
-1. Inapplicable
1. Believes a great deal immigrants should be sent back
2. Believes a moderate amount immigrants should be sent back
3. Believes a little immigrants should be sent back
4. Believes a little immigrants should be allowed to live & work in US
5. Believes a moderate amount immigrants should be allowed to live & work in US
6. Believes a great deal immigrants should be allowed to live & work in US

Survey Question(s)

IMMIG_CHILD, IMMIG_CHILDSTR

Question

Do you favor, oppose, or neither favor nor oppose building a wall on the U.S. border with Mexico?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

IMMIG_WALL

Question

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

IMMIG_WALLSTR

Universe

IF R FAVORS BUILDING A WALL ON THE U.S. BORDER WITH MEXICO /
IF R OPPOSES BUILDING A WALL ON THE U.S. BORDER WITH MEXICO:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241393 or V241394
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

IMMIG_WALL, IMMIG_WALLSTR

Question

How important do you think it is that everyone in the United States learn to speak English? [Very important, somewhat important, not very important, or not at all important / Not at all important, not very important, somewhat important, or very important?]

Value Labels

-9. Refused
-1. Inapplicable
1. Very important
2. Somewhat important
3. Not very important
4. Not at all important

Survey Question(s)

USLANG_SPEAKENG

Response Order

Forward/Reverse order

Question

What is the best way to deal with the problem of urban unrest and rioting? Some say it is more important to use all available force to maintain law and order, no matter what results. Others say it is more important to correct the problems of racism and police violence that give rise to the disturbances. And, of course, other people have opinions in between.

On this scale from 1 to 7, where 1 means solve problems of racism and police violence, and 7 means use all available force to maintain law and order, where would you place yourself on this scale, or haven’t you thought much about this?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Solve problems of racism and police violence
7. Use all available force to maintain law and order
99. Haven’t thought much about this

Survey Question(s)

PROTEST_UNREST

Question

Do you favor, oppose, or neither favor nor oppose the United States giving weapons to help Ukraine fight Russia?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

FORPOL_UKRAINE

Question

Do you (favor/oppose) that [a great deal, a moderate amount, or a little/ a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

FORPOL_UKRAINESTR

Universe

IF R FAVORS GIVING WEAPONS TO HELP UKRAINE /
IF R OPPOSES GIVING WEAPONS TO HELP UKRAINE:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241398 or V241399
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

FORPOL_UKRAINE, FORPOL_UKRAINESTR

Question

Do you favor, oppose, or neither favor nor oppose the United States giving military assistance to Israel?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

FORPOL_ISRAEL

Question

Do you (favor/oppose) that [a great deal, a moderate amount, or a little/ a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

FORPOL_ISRAELSTR

Universe

IF R FAVORS GIVING MILITARY ASSISTANCE TO ISRAEL /
IF R OPPOSES GIVING MILITARY ASSISTANCE TO ISRAEL:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241401 or V241402
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

FORPOL_ISRAEL, FORPOL_ISRAELSTR

Question

Do you favor or oppose, or neither favor nor oppose the United States providing humanitarian assistance to Palestinians in the Gaza Strip?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

FORPOL_GAZA

Question

Do you (favor/oppose) that [a great deal, a moderate amount, or a little/ a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

FORPOL_GAZASTR

Universe

IF R FAVORS HUMANITARIAN ASSISTANCE TO PALESTINIANS IN GAZA /
IF R OPPOSES HUMANITARIAN ASSISTANCE TO PALESTINIANS IN GAZA:

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241404 or V241405
-1. Inapplicable
1. Favor a great deal
2. Favor moderately
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose moderately
7. Oppose a great deal

Survey Question(s)

FORPOL_GAZA, FORPOL_GAZASTR

Question

In the Middle East conflict, do you side more with [the Israelis, the Palestinians/the Palestinians, the Israelis], both equally, or neither?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Israelis
2. Palestinians
3. Both equally
4. Neither

Survey Question(s)

FORPOL_ISRPAL

Question

How much more do you side with the [Israelis / Palestinians]? A little, a moderate amount, or a lot?

Value Labels

-9. Refused
-1. Inapplicable
1. A little
2. A moderate amount
3. A lot

Survey Question(s)

FORPOL_ISRPALSTR

Universe

IF R SIDES WITH ISRAELIS OR PALESTINIANS:

Value Labels

-2. DK/RF in V241407 or V241408
-1. Inapplicable
1. Side a lot with Israelis
2. Side a moderate amount with Israelis
3. Side a little with Israelis
4. Side with both equally
5. Side a little with Palestinians
6. Side a moderate amount with Palestinians
7. Side a lot with Palestinians
8. Side with neither

Survey Question(s)

FORPOL_ISRPAL, FORPOL_ISRPALSTR

Question

Do you approve, disapprove, or neither approve nor disapprove of the protests on college campuses against the war in Gaza?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Approve of the protests
2. Disapprove of the protests
3. Neither approve nor disapprove

Survey Question(s)

FORPOL_GAZAPROTEST

Question

How much do you [approve / disapprove] of the protests? A little, a moderate amount, or a lot?

Value Labels

-9. Refused
-1. Inapplicable
1. A little
2. A moderate amount
3. A lot

Survey Question(s)

FORPOL_GAZAPROTESTSTR

Universe

IF R APPROVES OF PROTESTS /
IF R DISAPPROVES OF PROTESTS:

Value Labels

-2. DK/RF in V241410 or V241411
-1. Inapplicable
1. Approve a lot of protests
2. Approve a moderate amount of protests
3. Approve a little of protests
4. Neither approve nor disapprove of protests
5. Disapprove a little of protests
6. Disapprove a moderate amount of protests
7. Disapprove a lot of protests

Survey Question(s)

FORPOL_GAZAPROTEST, FORPOL_GAZAPROTESTSTR

Question

Now on another topic: How important is religion in your life? [Extremely important, very important, moderately important, a little important, or not important at all? / Not important at all, a little important, moderately important, very important, or extremely important?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. A little important
5. Not important at all

Survey Question(s)

RELIG_RELIMPREV, PAPI PRE Q31

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Which of these statements comes closest to describing your feelings about the Bible? You can just give me the number of your choice.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. The Bible is the actual word of God and is to be taken literally, word for word
2. The Bible is the word of God but not everything in it should be taken literally, word for word
3. The Bible is a book written by men and is not the word of God
5. Other {SPECIFY}

Survey Question(s)

RELIG_RELBIBLE

Question

Which of these statements comes closest to describing your feelings about the Bible? You can just give me the number of your choice.

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

RELIG_RELBIBLE

Question

What is your present religion, if any?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Protestant
2. Roman Catholic
3. Orthodox Christian (such as Greek or Russian Orthodox)
4. Latter-Day Saints (LDS)
5. Jewish
6. Muslim
7. Buddhist
8. Hindu
9. Atheist
10. Agnostic
11. Something else
12. Nothing in particular

Survey Question(s)

RELIG_RELGRREV

Question

Would you say that is atheist, agnostic, Christian, or nothing in particular?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Atheist
2. Agnostic
3. Christian
4. Nothing in particular

Survey Question(s)

RELIG_RELGRNO

Universe

IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’:

Question

What specific religion, church or denomination is that?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_RELDENOM

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:

Question

What specific religion, church or denomination is that?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_RELDENOM

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:

Question

With which Baptist group is your church associated? Is it the Southern Baptist Convention, the American Baptist Churches in the U.S.A., the American Baptist Association, the National Baptist Convention, an independent Baptist church, or some other Baptist group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_BAPT

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS BAPTIST:

Question

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_BAPT

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS BAPTIST:

Question

Are you affiliated with any larger Baptist group or is this strictly a local church?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_INDBAPT

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS BAPTIST:
IF R’S CHURCH IS INDEPENDENT BAPTIST:

Question

Are you affiliated with any larger Baptist group or is this strictly a local church?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_INDBAPT

Universe

Question

Is this church part of the Evangelical Lutheran Church in America, the Missouri Synod, or some other Lutheran group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_LUTH

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS LUTHERAN:

Question

Is this church part of the Evangelical Lutheran Church in America, the Missouri Synod, or some other Lutheran group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_LUTH

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS LUTHERAN:

Question

Is your church part of the United Methodist Church, African Methodist Episcopal Church, African Methodist Episcopal Zion Church, or some other Methodist group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_METH

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS METHODIST:

Question

Is your church part of the United Methodist Church, African Methodist Episcopal Church, African Methodist Episcopal Zion Church, or some other Methodist group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_METH

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS METHODIST:

Question

Is this the Presbyterian Church in the U.S.A. or some other Presbyterian group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_PRESB

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS PRESBYTERIAN:

Question

Is this the Presbyterian Church in the U.S.A. or some other Presbyterian group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_PRESB

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS PRESBYTERIAN:

Question

Is this the Christian Reformed Church, the Reformed Church in America or some other Reformed group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_REFRM

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS REFORMED:

Question

Is this the Christian Reformed Church, the Reformed Church in America or some other Reformed group?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_REFRM

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS REFORMED:

Question

Is this the church of the Brethren, the Plymouth Brethren, or what?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_BRETHR

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS BRETHREN:

Question

Is this the church of the Brethren, the Plymouth Brethren, or what?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_BRETHR

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS BRETHREN:

Question

When you say ‘Christian’ does that mean the denomination called the ‘Christian Church Disciples of Christ,’ or some other Christian denomination, or do you mean to say ‘I am just a Christian’?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_DISCP

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R SAYS DENOMINATION IS ‘CHRISTIAN’:

Question

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_DISCP

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R SAYS DENOMINATION IS ‘CHRISTIAN’:

Question

Is this the Church of Christ or the United Church of Christ?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_CHCHRST

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS CHURCH OF CHRIST:

Question

Is this the Church of God of Anderson, Indiana; the Church of God of Cleveland, Tennessee; the Church of God in Christ; or some other Church of God?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_CHGOD

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS CHURCH OF GOD:

Question

Is this the Church of God of Anderson, Indiana; the Church of God of Cleveland, Tennessee; the Church of God in Christ; or some other Church of God?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_CHGOD

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS CHURCH OF GOD:

Question

What kind of church is that? What is it called exactly? Is that part of a larger church or denomination? What is the church called?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_PENT

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R DENOMINATION IS HOLINESS OR PENTECOSTAL:

Question

What is it called exactly? Is that church part of a denomination?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_DENOTHER

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ BUT FURTHER DESCRIBED AS CHRISTIAN:
IF R SPECIFIC DENOMINATION ‘OTHER’:

Question

Is that group Christian?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_OTHXIAN

Universe

IF R RELIGIOUS GROUP PROTESTANT OR ‘SOMETHING ELSE’ /
IF R RELIGIOUS GROUP ‘NOTHING IN PARTICULAR’ AND FURTHER DESCRIBED AS CHRISTIAN:
IF R SPECIFIC DENOMINATION ‘OTHER’:

Question

Do you consider yourself Orthodox, Conservative, Reform or what?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_JEWISH

Universe

IF R GAVE RELIGIOUS GROUP AS JEWISH :

Question

Do you consider yourself Orthodox, Conservative, Reform or what?

Value Labels

-3. RESTRICTED

Survey Question(s)

RELIG_JEWISH

Universe

IF R GAVE RELIGIOUS GROUP AS JEWISH :

Question

Lots of things come up that keep people from attending religious services even if they want to. Thinking about your life these days, do you ever attend religious services, apart from occasional weddings, baptisms or funerals?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

RELIG_CHURCH

Question

Do you go to religious services [every week, almost every week, once or twice a month, a few times a year, or never/ never, a few times a year, once or twice a month, almost every week, or every week]?

Value Labels

-9. Refused
-1. Inapplicable
1. Every week
2. Almost every week
3. Once or twice a month
4. A few times a year
5. Never

Survey Question(s)

RELIG_CHURCHOFT

Universe

IF R ATTENDS RELIGIOUS SERVICES:

Response Order

Forward/Reverse order

Question

Would you say you go to religious services once a week or more often than once a week?

Value Labels

-1. Inapplicable
1. Once a week
2. More often than once a week

Survey Question(s)

RELIG_CHURCHWK

Universe

IF R ATTENDS RELIGIOUS SERVICES:
IF R SAYS ATTENDS RELIGIOUS SERVICES ‘EVERY WEEK’:

Question

Would you call yourself a born-again Christian, that is, have you personally had a conversion experience related to Jesus Christ?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

RELIG_BORNAGN

Universe

IF R IS CHRISTIAN:

Question

Which of the following terms describe your religious beliefs?
- Charismatic/Pentecostal
- Traditional
- Mainline
- Progressive
- Non-traditional believer
- Secular
- Spiritual but not religious
- None of the above

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RELIG_RELIGIDENT

Value Labels

See APPENDIX A: RELIGION CODES for codes 010-889

Value Labels

-2. Missing: DK, RF, Did not specify
-1. Inapplicable
1. Mainline Protestant
2. Evangelical Protestant
3. Black Protestant
4. Undifferentiated Protestant
5. Roman Catholic
6. Other Christian
7. Jewish
8. Other religion
9. Not religious

Question

Now on another topic. How many family members are living with you?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
6. Six or more

Survey Question(s)

DEM_FINFAM

Question

We are interested in how people are getting along financially these days. Would you say that [you /you and your family living here] are [much better off financially, somewhat better off, about the same, somewhat worse off, or much worse off / much worse off financially, somewhat worse off, about the same, somewhat better off, or much better off] than you were a year ago?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Much better off
2. Somewhat better off
3. About the same
4. Somewhat worse off
5. Much worse off

Survey Question(s)

DEM_FINRETRO

Universe

IF R IS NOT LIVING AT HOME WITH FAMILY MEMBERS /
IF R IS LIVING AT HOME WITH 1 OR MORE FAMILY MEMBERS:

Response Order

Forward/Reverse order

Question

Now looking ahead, do you think that a year from now [you /you and your family living here] will be [much better off financially, somewhat better off, about the same, somewhat worse off, or much worse off / much worse off financially, somewhat worse off, about the same, somewhat better off, or much better off] than now?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Much better off
2. Somewhat better off
3. About the same
4. Somewhat worse off
5. Much worse off

Survey Question(s)

DEM_FINPROSP

Universe

IF R IS NOT LIVING AT HOME WITH FAMILY MEMBERS /
IF R IS LIVING AT HOME WITH 1 OR MORE FAMILY MEMBERS:

Response Order

Forward/Reverse order

Question

What is the month, day and year of your birth? MONTH:

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_BIRTHMO

Question

DAY:

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_BIRTHDY

Question

YEAR:

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_BIRTHYR

Question

What is your age and what is your date of birth? Print numbers in boxes.

Value Labels

-3. RESTRICTED

Survey Question(s)

PAPI PRE Q33

Question

What is your age and what is your date of birth? Print numbers in boxes.

Value Labels

-4. Error
-2. Missing, exact birth date not given
-1. Inapplicable
80. Eighty years old or older

Survey Question(s)

PAPI PRE Q33

Value Labels

-2. Missing, exact birth date not given
80. Eighty years old or older

Survey Question(s)

DEM_BIRTHMO, DEM_BIRTHDY, DEM_BIRTHYR, PAPI PRE Q33

Question

Are you now married, widowed, divorced, separated or never married?

Value Labels

-9. Refused
-1. Inapplicable
1. Married: spouse present
2. Married: spouse absent {VOL, FtF}
3. Widowed
4. Divorced
5. Separated
6. Never married

Survey Question(s)

DEM_MARITAL

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Married
2. Widowed
3. Divorced
4. Separated
5. Never married

Survey Question(s)

PAPI PRE Q38

Value Labels

-2. Missing in V241459 or V241460
1. Married
2. Widowed
3. Divorced
4. Separated
5. Never married

Survey Question(s)

DEM_MARITAL, PAPI PRE Q38

Question

Are you currently living with a partner, or not?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes, living with a partner
2. No, not living with a partner

Survey Question(s)

DEM_PARTN

Universe

IF R MARITAL STATUS IS NEVER MARRIED, WIDOWED, DIVORCED OR SEPARATED:

Question

What is the highest level of school you have completed or the highest degree you have received?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Less than 1st grade
2. 1st, 2nd, 3rd or 4th grade
3. 5th or 6th grade
4. 7th or 8th grade
5. 9th grade
6. 10th grade
7. 11th grade
8. 12th grade no diploma
9. High school graduate - High school diploma or equivalent (for example: GED)
10. Some college but no degree
11. Associate degree in college - Occupational/vocational program
12. Associate degree in college - Academic program
13. Bachelor’s degree (For example: BA, AB, BS)
14. Master’s degree (For example: MA, MS, MEng, MEd, MSW, MBA)
15. Professional school Degree (For example: MD,DDS,DVM,LLB,JD)
16. Doctorate degree (For example: PhD, EdD)
95. Other {SPECIFY}

Survey Question(s)

DEM_EDUCR

Question

What is the highest level of school you have completed or the highest degree you have received?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_EDUCR

Question

What is the highest level of school you have completed or the highest degree you received?

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Less than high school diploma
2. High school diploma or equivalent
3. Some college
4. Bachelor’s degree
5. Advanced degree above bachelor’s

Survey Question(s)

PAPI PRE Q39

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-2. Insufficent information to code other/specify open-ended response
1. Less than high school credential
2. High school credential
3. Some post-high school, no bachelor’s degree
4. Bachelor’s degree
5. Graduate degree

Survey Question(s)

DEM_EDUCR, PAPI PRE Q39

Variable Note

An additional 31 cases were coded and added to the education summary variable based on rother/specify responses given by the respondent.

Question

People can get a high school diploma in a variety of ways, such as graduating from high school or by getting a GED or other equivalent. How did you get your high school diploma?

Value Labels

-9. Refused
-1. Inapplicable
1. Graduation from High School
2. GED or other equivalent

Survey Question(s)

DEM_DIPGED

Universe

IF R’S HIGHEST EDUCATIONAL LEVEL IS DIPLOMA OR EQUIVALENT:

Question

What is the highest level of school your [husband or wife / partner] has completed or the highest degree your [husband or wife / partner] has received?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Less than 1st grade
2. 1st, 2nd, 3rd or 4th grade
3. 5th or 6th grade
4. 7th or 8th grade
5. 9th grade
6. 10th grade
7. 11th grade
8. 12th grade no diploma
9. High school graduate- High school diploma or equivalent (for example: GED)
10. Some college but no degree
11. Associate degree in college - Occupational/vocational program
12. Associate degree in college - Academic program
13. Bachelor’s degree (For example: BA, AB, BS)
14. Master’s degree (For example: MA, MS, Meng, Med, MSW, MBA)
15. Professional school Degree (For example: MD,DDS,DVM,LLB,JD)
16. Doctorate degree (For example: PhD, EdD)
95. Other {SPECIFY}

Survey Question(s)

DEM_EDUCSP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

What is the highest level of school your [husband or wife / partner] has completed or the highest degree your [husband or wife / partner] has received?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_EDUCSP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

How did your [husband or wife / partner] get their high school diploma?

Value Labels

-1. Inapplicable
1. Graduation from High School
2. GED or other equivalent

Survey Question(s)

DEM_DIPGEDSP

Universe

IF R IS MARRIED AND SPOUSE’S HIGHEST EDUCATIONAL LEVEL IS DIPLOMA OR EQUIVALENT /
IF R IS PARTNERED AND PARTNER’S HIGHEST EDUCATIONAL LEVEL IS DIPLOMA OR EQUIVALENT:

Value Labels

-9. Refused
-8. Don’t know
-2. Insufficent information to code other/specify open-ended response
-1. Inapplicable
1. Less than high school credential
2. High school credential
3. Some post-high school, no bachelor’s degree
4. Bachelor’s degree
5. Graduate degree

Survey Question(s)

DEM_EDUCSP

Question

Are you now serving on active duty in the U.S. armed forces – the U.S. Air Force, Army, Coast Guard, Marine Corps, Navy, or Space Force – or have you previously served on active duty in the U.S. armed forces, or have you never served on active duty in the U.S. armed forces?

Value Labels

-9. Refused
-1. Inapplicable
1. Now serving on active duty
2. Previously served on active duty but not now on active duty
3. Have never served on active duty

Survey Question(s)

DEM_ACTIVDUTY

Question

Last week, did you work for pay at a job (or business)?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No, did not work (or retired)

Survey Question(s)

DEM_JOB30A, PAPI PRE Q43

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Last week, did you do any work for pay, even for as little as one hour?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_JOB30B

Universe

IF INITIAL STATUS NOT WORKING NOW:

Question

Last week, were you on layoff from a job?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_JOB36A

Universe

IF INITIAL STATUS NOT WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW CONFIRMED:

Question

Last week, were you temporarily absent from a job or business? Reasons for temporary absence could include vacation, temporary illness, maternity leave or other family or personal reasons, bad weather, etc.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes, temporarily absent
2. No

Survey Question(s)

DEM_JOB36B

Universe

IF INITIAL STATUS NOT WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW CONFIRMED /
IF R NOT ON LAYOFF FROM JOB LAST WEEK:

Question

Have you been informed that you will be recalled to work within the next 6 months or been given a date to return to work?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_JOB36C

Universe

IF INITIAL STATUS NOT WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW CONFIRMED /
IF R IS ON LAYOFF FROM JOB LAST WEEK:

Question

During the last 4 weeks, have you been actively looking for work?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_JOB37

Universe

IF INITIAL STATUS NOT WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW CONFIRMED /
IF R IS ON LAYOFF FROM JOB LAST WEEK AND NOT GIVEN DATE TO RETURN TO WORK /
IF R NOT ON LAYOFF FROM JOB LAST WEEK AND NOT TEMPORARILY ABSENT FROM JOB:

Question

Last week, could you have started a job if offered one, or returned to work if recalled?

Value Labels

-1. Inapplicable
1. Yes, could have gone to work
2. No, could not have gone to work

Survey Question(s)

DEM_JOB38

Universe

IF INITIAL STATUS NOT WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW CONFIRMED /
IF R IS ON LAYOFF FROM JOB LAST WEEK AND GIVEN DATE TO RETURN TO WORK /
IF R IS ON LAYOFF FROM JOB LAST WEEK AND NOT GIVEN DATE TO RETURN TO WORK AND ACTIVELY LOOKING FOR WORK /
IF R NOT ON LAYOFF FROM JOB LAST WEEK AND NOT TEMPORARILY ABSENT FROM JOB AND ACTIVELY LOOKING FOR WORK:

Question

When did you last work, even for a few days? Within the past 12 months, 1 to 5 years ago, over 5 years ago, or never worked?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Within the past 12 months
2. 1 to 5 years ago
3. Over 5 years ago
4. Never worked

Survey Question(s)

DEM_JOB39

Universe

IF INITIAL STATUS NOT WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW CONFIRMED /
IF R IS NOT ON LAYOFF FROM JOB AND TEMPORARILY ABSENT /
IF R IS NOT ON LAYOFF FROM JOB LAST WEEK AND NOT TEMPORARILY ABSENT FROM JOB AND NOT ACTIVELY LOOKING FOR WORK /
IF R IS NOT ON LAYOFF FROM JOB AND NOT TEMPORARILY ABSENT FROM JOB AND ACTIVELY LOOKING FOR WORK AND COULD OR COULD NOT HAVE WORKED LAST WEEK /
IF R IS ON LAYOFF FROM JOB LAST WEEK AND GIVEN DATE TO RETURN TO WORK AND COULD OR COULD NOT HAVE WORKED LAST WEEK /
IF R IS ON LAYOFF FROM JOB LAST WEEK AND NOT GIVEN DATE TO RETURN TO WORK AND ACTIVELY LOOKING FOR WORK AND COULD OR COULD NOT HAVE WORKED LAST WEEK /
IF R IS ON LAYOFF FROM JOB LAST WEEK AND NOT GIVEN DATE TO RETURN TO WORK AND NOT ACTIVELY LOOKING FOR WORK:

Question

During the past 12 months, 52 weeks, did you work every week? Count paid vacation, paid sick leave, and military service as work.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_JOB40A

Universe

IF INITIAL STATUS WORKING WORKING NOW /
IF INITIAL STATUS NOT WORKING BUT R DETERMINED TO BE WORKING NOW /
IF R WORKED AT ALL WITHIN PAST 12 MONTHS:

Question

During the past 12 months, 52 weeks, how many weeks did you work? Include paid time off and include weeks when you only worked for a few hours.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

DEM_JOB40B

Universe

IF INITIAL STATUS WORKING WORKING NOW /
IF INITIAL STATUS NOT WORKING BUT R DETERMINED TO BE WORKING NOW /
IF R WORKED AT ALL IN PAST 12 MONTHS /
IF R DID NOT WORK EVERY WEEK PAST 12 MONTHS:

Question

During the past 12 months, in the weeks worked, how many hours did you usually work each week?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

DEM_JOB41

Universe

IF INITIAL STATUS WORKING WORKING NOW AND R WORKED EVERY WEEK IN PAST 12 MONTHS /
IF INITIAL STATUS WORKING WORKING NOW AND R DID NOT WORK EVERY WEEK IN PAST 12 MONTHS AND R WORKED AT LEAST 1 WEEK /
IF INITIAL STATUS NOT WORKING BUT R DETERMINED TO BE WORKING NOW AND WORKED EVERY WEEK IN PAST 12 MONTHS/
IF INITIAL STATUS NOT WORKING BUT R DETERMINED TO BE WORKING NOW AND AND R DID NOT EVERY WEEK IN PAST 12 MONTHS AND R WORKED AT LEAST 1 WEEK/
IF R WORKED AT ALL IN PAST 12 MONTHS AND R WORKED EVERY WEEK IN PAST 12 MONTHS /
IF R WORKED AT ALL IN PAST 12 MONTHS AND R DID NOT WORK EVERY WEEK IN PAST 12 MONTHS AND R WORKED AT LEAST 1 WEEK:

Question

Is that more hours than you want to work, fewer hours than you want to work, or generally about right?

Value Labels

-9. Refused
-1. Inapplicable
1. More
2. Fewer
3. About right

Survey Question(s)

DEM_OKHRSNOW

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R DETERMINED TO BE WORKING NOW /
IF NUMBER OF HOURS WORKED GREATER THAN ZERO:

Question

IF WORKED IN LAST WEEK: The next series of questions is about the type of employment you have had last week. If you had more than one job, describe the one at which the most hours were worked.

IF DID NOT WORK IN THE LAST WEEK: Please describe your most recent employment.

Which one of the following best describes your employment?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. For-profit company or organization
2. Non-profit organization (including tax-exempt and charitable organizations)
3. Local government (for example: city or county school district)
4. State government (including state colleges/universities)
5. Active duty US Armed Forces or Commissioned Corps
6. Federal government civilian employee
7. Owner of non-incorporated business, professional practice, or farm
8. Owner of incorporated business, professional practice, or farm
9. Worked without pay in a for-profit family business or farm for 15 hours or more per week

Survey Question(s)

DEM_JOB42A

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R DETERMINED TO BE WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT WORKED IN THE PAST:

Question

What kind of business or industry is this? Include the main activity, product, or service provided at the location where employed. For example: elementary school, or residential construction.

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_JOB42C

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R DETERMINED TO BE WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT WORKED IN THE PAST:

Question

What is your main occupation? For example, 4th grade teacher, entry-level plumber.

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_JOB42E

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R DETERMINED TO BE WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT WORKED IN THE PAST /
IF INDUSTRY IS NOT DK/RF

Question

What are your most important activities or duties?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_JOB42F

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R DETERMINED TO BE WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT WORKED IN THE PAST /
IF INDUSTRY IS NOT DK/RF /
IF MAIN OCCUPATION IS NOT DK/RF:

Value Labels

-2. Missing: RF/DK
-1. Inapplicable
1. R working now (if also retired, disabled, homemaker or student, working 20 or more hrs/wk)
2. R temporarily laid off
4. R unemployed
5. R retired (if also working, working < 20 hrs/wk)
6. R permanently disabled (if also working, working < 20 hrs/wk)
7. R homemaker (if also working, working <20 hrs/wk/incl nonworkg rs both homemaker and student)
8. R student (if also working, working <20 hrs/wk)

Question

We’d like to know if you now consider yourself a homemaker, retired, permanently disabled, or a full time student. You may choose more than one, or none.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_STATUS

Universe

Question

We’d like to know if you now consider yourself a homemaker, retired, permanently disabled, or a full time student. You may choose more than one, or none.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_STATUS

Universe

Question

We’d like to know if you now consider yourself a homemaker, retired, permanently disabled, or a full time student. You may choose more than one, or none.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_STATUS

Universe

Question

We’d like to know if you now consider yourself a homemaker, retired, permanently disabled, or a full time student. You may choose more than one, or none.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_STATUS

Universe

Question

We’d like to know if you now consider yourself a homemaker, retired, permanently disabled, or a full time student. You may choose more than one, or none.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_STATUS

Universe

Question

What year did you retire?

YEAR:

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable

Survey Question(s)

DEM_RETIREYR

Universe

IF R INITIAL STATUS RETIRED:

Question

Were you out of work or laid off at any time during the last six months?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_OFFWORK

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R IS DETERMINED TO BE CURRENTLY WORKING
IF R IS TEMPORARILY ABSENT /
IF R HAS WORKED IN PAST 12 MONTHS:

Question

How worried are you about losing your job in the near future? [Not at all, a little, moderately, very, or extremely worried / Extremely, very, moderately, a little, or not at all worried]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

DEM_LOSEJOB

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R IS DETERMINED TO BE CURRENTLY WORKING /
IF R ON LAYOFF FROM A JOB /
IF R TEMPOARILY ABSENT FROM JOB:

Response Order

Forward/Reverse order

Question

During the last six months, have you had a reduction in your work hours or had to take a cut in pay at any time for reasons other than illness or personal choice?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Reduced hours or pay in the last 6 months
2. Neither reduced hours nor reduced pay in last 6 months

Survey Question(s)

DEM_HRSREDUCE

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R IS DETERMINED TO BE CURRENTLY WORKING /
IF R ON LAYOFF FROM A JOB /
IF R TEMPOARILY ABSENT FROM JOB:

Question

Overall, how satisfied or dissatisfied are you with your current job?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely satisfied
2. Moderately satisfied
3. Slightly satisfied
4. Neither satisfied nor dissatisfied
5. Slightly dissatisfied
6. Moderately dissatisfied
7. Extremely dissatisfied

Survey Question(s)

DEM_JOBSAT

Universe

IF INITIAL STATUS IS WORKING NOW /
IF INITIAL STATUS NOT WORKING NOW BUT R DETERMINED TO BE WORKING NOW:

Question

We’d like to know about your [husband or wife / partner]. Is your [husband or wife / partner] working now, temporarily laid off, or is your [husband or wife /partner] unemployed, retired, permanently disabled, a homemaker, a student, or what?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_EMPTYPESP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_EMPTYPESP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_EMPTYPESP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_EMPTYPESP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_EMPTYPESP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_EMPTYPESP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_EMPTYPESP

Universe

IF R IS MARRIED/
IF R IS PARTNERED:

Question

What is your [spouse’s/partner’s] main occupation? (What kind of work does your [spouse/partner] do? What are the most important activities or duties?)

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_CSESJOBSP

Universe

IF R IS MARRIED/PARTNERED AND HAS MENTIONED SPOUSE/PARTNER IS WORKING:

Question

Do you or anyone else in this household belong to a labor union or to an employee association similar to a union?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_UNION

Question

Who is it that belongs?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_UNIONWHO

Universe

IF SOMEONE IN HOUSEHOLD BELONGS TO LABOR UNION:

Question

Who is it that belongs?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_UNIONWHO

Universe

IF SOMEONE IN HOUSEHOLD BELONGS TO LABOR UNION:

Question

Who is it that belongs?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM_UNIONWHO

Universe

IF SOMEONE IN HOUSEHOLD BELONGS TO LABOR UNION:

Question

Are you of Hispanic, Latino, or Spanish origin?

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_HISP, PAPI PRE Q35

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

I am going to read you a list of five race categories. You may choose one or more races. For this survey, Hispanic origin is not a race. Are you White; Black or African American; American Indian or Alaska Native; Asian; or Native Hawaiian or Other Pacific Islander?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPS, PAPI PRE Q36

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPS, PAPI PRE Q36

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPS, PAPI PRE Q36

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPS, PAPI PRE Q36

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPS, PAPI PRE Q36

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Value Labels

-9. Refused
-8. Don’t know
-4. Error
1. White, non-Hispanic
2. Black, non-Hispanic
3. Hispanic
4. Asian or Native Hawaiian/other Pacific Islander, non-Hispanic
5. Native American/Alaska Native or other race, non-Hispanic
6. Multiple races, non-Hispanic

Survey Question(s)

DEM_HISP, DEM_RACECPS

Question

Are you of Middle Eastern or North African descent?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_MENA

Question

What do you consider your main ethnic group or nationality group? (For example: Italian, Jamaican, African American, Cambodian, Cape Verdean, Norwegian, Dominican, French Canadian, Haitian, Korean, Lebanese, Polish, Nigerian, Mexican, Taiwanese, Ukrainian, and so on.)

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_ETHNIC

Question

ENTER NUMBER OF ETHNIC GROUPS MENTIONED BY R:

Value Labels

-1. Inapplicable
0. None (incl DK) and R did not refuse or indicate no knowledge of own ethnicity
1. One
2. More than one (two or more)
3. Respondent refused to answer or R said no knowledge of own ethnicity

Survey Question(s)

DEM_NUMETH

Universe

IF MODE IS FTF:

Question

With which of these groups do you most closely identify?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_MOSTETH

Universe

IF R MENTIONED MORE THAN 1 NATIONALITY/ETHNIC GROUP:

Question

Where were your parents born? Were they both born in the U.S., was only one born in the U.S., or were both born in another country?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Both parents born in the US
2. One parent born in the US
3. Both parents born in another country

Survey Question(s)

DEM_PARENTS

Question

In what state, country, or territory were you born?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. A US state or Washington DC
2. Puerto Rico
3. Another US territory
4. Another country {SPECIFY}

Survey Question(s)

DEM_BIRTHPLACE

Question

In what state, country, or territory were you born?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_BIRTHPLACE

Question

Are you a U.S. citizen, or a citizen of another country? Mark all that apply.

Value Labels

-9. Refused
-1. Inapplicable
1. United States citizen
2. Citizen of another country
3. Both

Survey Question(s)

PAPI PRE Q37

Question

How many of your grandparents, if any, were born outside the U.S.?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
0. None
1. One
2. Two
3. Three
4. All

Survey Question(s)

DEM_GPAR

Question

Families of Hispanic or Latino background in the United States come from many different places. Which Spanish-speaking or Latin American country or territory does most of your family come from?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_HISPCNTRYREV

Universe

IF R IS HISPANIC:

Question

Families of Hispanic or Latino background in the United States come from many different places. Which Spanish-speaking or Latin American country or territory does most of your family come from?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_HISPCNTRYREV

Universe

IF R IS HISPANIC:

Question

You said your family comes from [DEM_HISPCNTRYREV]. Which one of these does most of your family come from?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_HISPCNTRYMOST

Universe

IF R IS HISPANIC:
IF MORE THAN 1 ANSWER OTHER THAN DK/RF GIVEN AS COUNTRIES OF ANCESTRY:

Value Labels

-9. Refused
-8. Don’t know
1. Mexican
2. Puerto Rican
3. Other Hispanic (one or more mentions)
4. Hispanic, type not determined
7. Not Hispanic

Question

Do you or your family trace any of your ancestry to Mexico?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_HISPMEX

Universe

IF R IS HISPANIC: IF R MENTIONS HISPANIC ANCESTRY AS SPAIN, U.S. OR UNLISTED ‘OTHER’ COUNTRY:

Question

When did you first arrive to live in the U.S.?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_HISPARR

Universe

IF R WAS NOT BORN IN THE U.S.:

Question

In what year did you become a naturalized U.S. citizen?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_HISPCIT

Universe

IF R WAS NOT BORN IN THE U.S., PUERTO RICO, OR U.S. TERRITORY:

Question

What language do you primarily speak at home with your family? Is it only English, mostly English, both languages equally, mostly Spanish, or only Spanish?

Value Labels

-9. Refused
-1. Inapplicable
1. Only English
2. Mostly English
3. Both languages equally
4. Mostly Spanish
5. Only Spanish

Survey Question(s)

DEM_HISPLANG

Universe

IF R INDICATES SELF AS SPANISH, HISPANIC, OR LATINO:

Question

Is your [spouse / partner / most recent former spouse] of Hispanic, Latino, or Spanish origin?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM_HISPSP

Universe

IF R IS MARRIED, R IS PARTNERED, R IS WIDOWED, DIVORCED, OR SEPARATED:

Question

Is your [spouse / partner / most recent former spouse] White; Black or African American; American Indian or Alaska Native; Asian; or Native Hawaiian or Other Pacific Islander?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPSSP

Universe

IF R IS MARRIED, R IS PARTNERED, R IS WIDOWED, DIVORCED, OR SEPARATED:

Question

Is your [spouse / partner / most recent former spouse] White; Black or African American; American Indian or Alaska Native; Asian; or Native Hawaiian or Other Pacific Islander?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPSSP

Universe

IF R IS MARRIED, R IS PARTNERED, R IS WIDOWED, DIVORCED, OR SEPARATED:

Question

Is your [spouse / partner / most recent former spouse] White; Black or African American; American Indian or Alaska Native; Asian; or Native Hawaiian or Other Pacific Islander?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPSSP

Universe

IF R IS MARRIED, R IS PARTNERED, R IS WIDOWED, DIVORCED, OR SEPARATED:

Question

Is your [spouse / partner / most recent former spouse] White; Black or African American; American Indian or Alaska Native; Asian; or Native Hawaiian or Other Pacific Islander?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPSSP

Universe

IF R IS MARRIED, R IS PARTNERED, R IS WIDOWED, DIVORCED, OR SEPARATED:

Question

Is your [spouse / partner / most recent former spouse] White; Black or African American; American Indian or Alaska Native; Asian; or Native Hawaiian or Other Pacific Islander?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM_RACECPSSP

Universe

IF R IS MARRIED, R IS PARTNERED, R IS WIDOWED, DIVORCED, OR SEPARATED:

Value Labels

-9. Refused
-1. Inapplicable
1. White, non-Hispanic
2. Black, non-Hispanic
3. Hispanic
4. Asian or Native Hawaiian/other Pacific Islander, non-Hispanic
5. Native American/Alaska Native or other race, non-Hispanic
6. Multiple races, non-Hispanic

Survey Question(s)

DEM_HISPSP, DEM_RACECPSSP

Question

What is the gender of your [spouse / partner / most recent former spouse]?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Male
2. Female
3. Something else

Survey Question(s)

DEM_GENDSP

Universe

IF R IS MARRIED, R IS PARTNERED, R IS WIDOWED, DIVORCED, OR SEPARATED:

Question

How many children or teenagers age 0 to 17 live in this household?

Value Labels

-9. Refused
-1. Inapplicable
0. No children
1. One child
2. Two children
3. Three children
4. Four children
5. Five children
6. Six children
7. Seven children
8. Eight children
9. More than eight children

Survey Question(s)

DEM2_HHCHILD, PAPI PRE Q32

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

[Are the children in your household/ Is the child in your household] enrolled in public school, private religious school, private non-religious school, or home school, or not in school?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM2_SCHENRL

Universe

IF THERE ARE MORE THAN 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD / IF THERE IS 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD:

Question

[Are the children in your household/ Is the child in your household] enrolled in public school, private religious school, private non-religious school, or home school, or not in school?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM2_SCHENRL

Universe

IF THERE ARE MORE THAN 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD / IF THERE IS 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD:

Question

[Are the children in your household/ Is the child in your household] enrolled in public school, private religious school, private non-religious school, or home school, or not in school?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM2_SCHENRL

Universe

IF THERE ARE MORE THAN 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD / IF THERE IS 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD:

Question

[Are the children in your household/ Is the child in your household] enrolled in public school, private religious school, private non-religious school, or home school, or not in school?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM2_SCHENRL

Universe

IF THERE ARE MORE THAN 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD / IF THERE IS 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD:

Question

[Are the children in your household/ Is the child in your household] enrolled in public school, private religious school, private non-religious school, or home school, or not in school?

Value Labels

-9. Refused
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

DEM2_SCHENRL

Universe

IF THERE ARE MORE THAN 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD / IF THERE IS 1 CHILD AGE 17 OR YOUNGER IN HOUSEHOLD:

Question

[Do you / Does anyone in this household, including you,] use the Internet at home? This includes accessing the Internet with a cell phone, computer, tablet, or other device.

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM2_INETHOME

Universe

IF R IS ONLY HOUSEHOLD MEMBER / IF R IS NOT ONLY HOUSEHOLD MEMBER :

Question

[Do you / Does anyone in this household, including you,] use the Internet at any other location?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM2_INETANY

Universe

IF NO INTERNET IN THE HOME
IF R IS ONLY HOUSEHOLD MEMBER / IF R IS NOT ONLY HOUSEHOLD MEMBER:

Question

Is there at least one telephone inside your home that is currently working and is not a cell phone?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM2_PHLAND

Question

Do you have a working cell phone?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM2_CELLPERS

Question

Do you live with anyone at your home who has a working cell phone?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM2_PHCELLHH

Universe

IF R DOES NOT HAVE A WORKING CELL PHONE AND R IS NOT THE ONLY HOUSEHOLD MEMBER:

Question

[Do you / Does anyone in this household, including you,] have a cell phone that will run apps and connect to the Internet, like an iPhone or Android?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

DEM2_PHINTERNET

Universe

IF R HAS A CELL PHONE OR ANYONE IN THE HOUSE HAS A CELL PHONE
IF R IS ONLY HOUSEHOLD MEMBER / IF R IS NOT ONLY HOUSEHOLD MEMBER:

Question

In what state, country, or territory did you mainly grow up?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Alabama  2. Alaska  4. Arizona
5. Arkansas  6. California  8. Colorado
9. Connecticut  10. Delaware
11. District of Columbia (Washington DC)
12. Florida  13. Georgia   15. Hawaii
16. Idaho   17. Illinois   18. Indiana
19. Iowa   20. Kansas   21. Kentucky
22. Louisiana   23. Maine   24. Maryland
25. Massachusetts   26. Michigan   27. Minnesota
28. Mississippi   29. Missouri   30. Montana
31. Nebraska   32. Nevada   33. New Hampshire
34. New Jersey   35. New Mexico   36. New York
37. North Carolina   38. North Dakota   39. Ohio
40. Oklahoma   41. Oregon   42. Pennsylvania
44. Rhode Island   45. South Carolina   46. South Dakota
47. Tennessee   48. Texas   49. Utah
50. Vermont   51. Virginia   53. Washington
54. West Virginia   55. Wisconsin   56. Wyoming
57. Puerto Rico   58. Another U.S. territory (Guam, Samoa, U.S. Virgin Islands)
59. Another country {SPECIFY}

Survey Question(s)

DEM3_GREWUP

Question

In what state, country, or territory did you mainly grow up?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM3_GREWUP

Question

Are your living quarters owned or being bought by a household member, rented for cash, or occupied without payment of cash rent?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
1. Owned or being bought by a household member
2. Rented for cash
3. Occupied without payment of cash rent

Survey Question(s)

DEM3_HOMECPS, PAPI PRE Q40

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Does your household make monthly mortgage payments for your home, or is the home owned outright with no payments due?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Pay mortgage
2. Own home with no payments due

Survey Question(s)

DEM3_HOMECPSOWN

Universe

IF R’S HOME OWNED OR BEING BOUGHT BY HOUSEHOLD MEMBER:

Question

Has your name ever changed or have you never changed your first or last name?

Value Labels

-9. Refused
-1. Inapplicable
1. Have changed name
2. Never changed name

Survey Question(s)

DEM3_NAMECH

Question

What year did you most recently change your name?

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM3_NAMECHYR

Universe

IF R HAS CHANGED NAME:

Question

How many years have you lived at this address?

Value Labels

-9. Refused
-8. Don’t know
-4. Error
-1. Inapplicable
1. 0 to 5 years
2. 6 to 10 years
3. 11 to 15 years
4. 16 to 20 years
5. More than 20 years

Survey Question(s)

DEM3_LENADDR, PAPI PRE Q3

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Where did you live five years ago? Please tell me the city, state, and ZIP code if you remember it.

Value Labels

-3. RESTRICTED

Survey Question(s)

DEM3_ADD5YR

Universe

IF R HAS LIVED AT CURRENT ADDRESS LESS THAN 5 YEARS:

Question

Do you have a non-expired Driver’s License?

Value Labels

-9. Refused
-1. Inapplicable
1. Have a non-expired driver’s license
2. Do not have one

Survey Question(s)

DEM3_DRIVLIC

Question

Do you have a valid, non-expired U.S. passport, or do you not have one?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Have a valid, non-expired US passport
2. Do not have one

Survey Question(s)

DEM3_PASSPORT

Question

Do you have any form of non-expired, government issued photo ID, such as a state ID card or military ID?

Value Labels

-1. Inapplicable
1. Have another form of ID
2. Do not have one

Survey Question(s)

DEM3_OTHGOVTID

Universe

IF R DOES NOT HAVE NONEXPIRED DRIVERS LICENSE:
IF R DOES NOT HAVE NONEXPIRED PASSPORT:

Question

So far as you and your family are concerned, how worried are you about your current financial situation? [Extremely worried, very worried, moderately worried, a little worried, or not at all worried / Not at all worried, a little worried, moderately worried, very worried, or extremely worried?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely worried
2. Very worried
3. Moderately worried
4. A little worried
5. Not at all worried

Survey Question(s)

ECPERIL_WORRYFIN, PAPI PRE Q42

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

During the next 12 months, how likely is it that you will be able to make all of your [rent/mortgage] payments on time? [Extremely likely, very likely, moderately likely, slightly likely, or not likely at all / Not likely at all, slightly likely, moderately likely, very likely, or extremely likely?]

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Extremely likely
2. Very likely
3. Moderately likely
4. Slightly likely
5. Not likely at all

Survey Question(s)

ECPERIL_PAYHOUSE

Universe

IF R PAYS RENT/
IF R OWNS HIS OR HER HOME AND PAYS A MORTGAGE:

Response Order

Forward/Reverse order

Question

During the past 12 months, has anyone in your family or a close personal friend lost a job, or has no one in your family and no close personal friend lost a job in the past 12 months?

Value Labels

-9. Refused
-8. Don’t know
-1. Inapplicable
1. Someone lost a job
2. No one lost a job

Survey Question(s)

ECPERIL_LOSTJOBS

Question

What is your sex?

Value Labels

-9. Refused
-4. Error
1. Male
2. Female

Survey Question(s)

SELFGEND_GENDTYP, PAPI PRE Q34

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

What is your gender?

Value Labels

-9. Refused
-1. Inapplicable
1. Man
2. Woman
3. Nonbinary
4. Something else, please specify

Survey Question(s)

SELFGEND_GENDMULTI

Question

What is your gender?

Value Labels

-3. RESTRICTED

Survey Question(s)

SELFGEND_GENDMULTI

Question

Do you consider yourself to be transgender?

Value Labels

-9. Refused
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

SELFGEND_TRANS

Question

Do you consider yourself to be heterosexual or straight, homosexual or gay, or bisexual?/ Do you consider yourself to be heterosexual or straight, homosexual or gay or lesbian, or bisexual?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Heterosexual or straight
2. Homosexual or gay (or lesbian)
3. Bisexual
4. Something else {SPECIFY}

Survey Question(s)

ORIENTN_RGAY

Universe

IF R IS NOT FEMALE /
IF R IS FEMALE:

Question

Do you consider yourself to be heterosexual or straight, homosexual or gay, or bisexual?/ Do you consider yourself to be heterosexual or straight, homosexual or gay or lesbian, or bisexual?

Value Labels

-3. RESTRICTED

Survey Question(s)

ORIENTN_RGAY

Universe

IF R IS NOT FEMALE /
IF R IS FEMALE:

Question

Do you personally, or jointly with a spouse, have any money invested in the stock market right now – either in an individual stock or in a mutual fund?

Value Labels

-9. Refused
-8. Don’t know
-5. Break off, sufficient partial
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

WEALTH_STOCKS

Question

The next question is about [the total combined income of all members of your family / your total income] during the past 12 months. This includes money from jobs, net income from business, farm or rent, pensions, dividends, interest, Social Security payments, and any other money income received by members of your family who are 15 years of age or older. What was the total income of your family during the past 12 months?

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTINC

Universe

IF R IS NOT ONLY MEMBER OF R’S FAMILY IN RESIDENCE IN R’S HOUSEHOLD /
IF R IS ONLY MEMBER OF R’S FAMILY IN RESIDENCE IN HOUSEHOLD:

Question

Was it $40,000 or more, or less than that?

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTMISS40

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):

Question

Was it $20,000 or more, or less than that?

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTMISS20

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME LESS THAN $40,000:

Question

Please choose the answer that includes the income of all members of your family during the past 12 months before taxes.

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTL20

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME LESS THAN $40,000:
IF R INDICATED INCOME LESS THAN $20,000:

Question

Please choose the answer that includes the income of all members of your family during the past 12 months before taxes.

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTG20L40

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME LESS THAN $40,000:
IF R INDICATED INCOME $20,000 OR MORE:

Question

Was it $70,000 or more, or less than that?

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTMISS70

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME $40,000 OR MORE:

Question

Please choose the answer that includes the income of all members of your family during the past 12 months before taxes.

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTG40L70

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME $40,000 OR MORE:
IF R INDICATED INCOME LESS THAN $70,000:

Question

Was it $100,000 or more, or less than that?

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTMISS100

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME $40,000 OR MORE:
IF R INDICATED INCOME $70,000 OR MORE:

Question

Please choose the answer that includes the income of all members of your family during the past 12 months before taxes.

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTG70L100

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME $40,000 OR MORE:
IF R INDICATED INCOME $70,000 OR MORE:
IF R INDICATED INCOME LESS THAN $100,000:

Question

Please choose the answer that includes the income of all members of your family during the past 12 months before taxes.

Value Labels

-3. RESTRICTED

Survey Question(s)

INC_TOTG100

Universe

IF TOTAL INCOME NUMBER SKIPPED TWICE (IMPLIED REFUSALS):
IF R INDICATED INCOME $40,000 OR MORE:
IF R INDICATED INCOME $70,000 OR MORE:
IF R INDICATED INCOME $100,000 OR MORE:

Question

What is the total income of your family during the past 12 months? If you are not completely sure, please give your best guess.

Value Labels

-3. RESTRICTED
1. Under $9,999
2. $10,000 to $29,999
3. $30,000 to $59,999
4. $60,000 to $99,999
5. $100,000 to $249,999
6. $250,000 or more

Survey Question(s)

PAPI PRE Q41

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
1. Under $5,000
2. $5,000-9,999
3. $10,000-12,499
4. $12,500-14,999
5. $15,000-17,499
6. $17,500-19,999
7. $20,000-22,499
8. $22,500-24,999
9. $25,000-27,499
10. $27,500-29,999
11. $30,000-34,999
12. $35,000-39,999
13. $40,000-44,999
14. $45,000-49,999
15. $50,000-54,999
16. $55,000-59,999
17. $60,000-64,999
18. $65,000-69,999
19. $70,000-74,999
20. $75,000-79,999
21. $80,000-89,999
22. $90,000-99,999
23. $100,000-109,999
24. $110,000-124,999
25. $125,000-149,999
26. $150,000-174,999
27. $175,000-249,999
28. $250,000 or more

Survey Question(s)

INC_TOTINC, INC_TOTL20, INC_TOTG20L40, INC_TOTG40L70, INC_TOTG70L100, INC_TOTG100

Variable Note

PAPI cases not included in this income summary variable due to differing response options. Income data for PAPI cases are included in V241567x

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
1. Under $9,999
2. $10,000 to $29,999
3. $30,000 to $59,999
4. $60,000 to $99,999
5. $100,000 to $249,999
6. $250,000 or more

Survey Question(s)

INC_TOTINC, INC_TOTL20, INC_TOTG20L40, INC_TOTG40L70, INC_TOTG70L100, INC_TOTG100, Q41

Question

In the past year, have you done any of the following? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

FINANCE_INFLBEHAV

Question

In the past year, have you done any of the following? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

FINANCE_INFLBEHAV

Question

In the past year, have you done any of the following? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

FINANCE_INFLBEHAV

Question

In the past year, have you done any of the following? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

FINANCE_INFLBEHAV

Question

In the past year, have you done any of the following? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

FINANCE_INFLBEHAV

Question

In the past year, have you done any of the following? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

FINANCE_INFLBEHAV

Question

How much money do you currently owe in student loans? If you are not sure, please provide your best guess. If none, type 0.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable

Survey Question(s)

FINANCE_STDLOAN

Universe

IF R HAS MORE THAN HIGH SCHOOL DIPLOMA OR EQUIVALENT:

Question

On another topic: In the past week, how often have you had trouble keeping your mind on what you were doing?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. All the time
2. Often
3. Sometimes
4. Rarely
5. Never

Survey Question(s)

MENTALHLTH_TRBLCONC

Response Order

Forward/Reverse order

Question

Do you presently have any kind of health insurance?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

HLTH_HAVEHINS

Question

How concerned are you about losing your health insurance in the next year?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Not at all concerned
2. A little concerned
3. Moderately concerned
4. Very concerned
5. Extremely concerned

Survey Question(s)

HLTH_LOSEINS

Universe

IF R HAS HEALTH INSURANCE:

Response Order

Forward/Reverse order

Question

How concerned are you about being able to pay health care expenses for you and your family in the next year?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Not at all concerned
2. A little concerned
3. Moderately concerned
4. Very concerned
5. Extremely concerned

Survey Question(s)

HLTH_COSTHLTH

Response Order

Forward/Reverse order

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Do you have any of the following disabilities or chronic conditions? Mark all that apply.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

HLTH_HEALTHID

Question

Over the last two weeks, how often have you been bothered by feeling little interest or pleasure in doing things?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. None of the time
2. Some of the time
3. About half the time
4. Most of the time
5. All of the time

Survey Question(s)

HLTH_DEPRESS1

Question

Over the last two weeks, how often have you been bothered by feeling down, depressed, or hopeless?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. None of the time
2. Some of the time
3. About half the time
4. Most of the time
5. All of the time

Survey Question(s)

HLTH_DEPRESS2

Question

Some people think that the way people talk needs to change with the times to be more sensitive to people from different backgrounds. Others think that this has already gone too far and many people are just too easily offended. Which is closer to your opinion?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. The way people talk needs to change a lot
2. The way people talk needs to change a little
3. People are a little too easily offended
4. People are much too easily offended

Survey Question(s)

POLCORRECT_CHGOFFEND

Question

How often do you stop yourself from saying something because you think someone might call you a racist, a sexist, or otherwise a bad person?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Never
2. Rarely
3. Occasionally
4. Fairly often
5. Very often

Survey Question(s)

POLCORRECT_SELFCENSOR

Question

On another topic: How much do you feel it is justified for people to use violence to pursue their political goals in this country?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Not at all
2. A little
3. A moderate amount
4. A lot
5. A great deal

Survey Question(s)

POLVIOL_JUSTIFIED

Response Order

Forward/Reverse order

Question

Compared to four years ago, do you think violence used to pursue political goals in the United States has:

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Increased
2. Decreased
3. Stayed the same

Survey Question(s)

POLVIOL_VIOLENCE

Question

Has it [increased/decreased] [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

POLVIOL_VIOLENCESTR

Response Order

Forward/Reverse order

Value Labels

-2. DK/RF in V241580 or V241580
-1. Inapplicable
1. Increased a great deal
2. Increased a moderate amount
3. Increased a little
4. Stayed the same
5. Decreased a little
6. Decreased a moderate amount
7. Decreased a great deal

Survey Question(s)

POLVIOL_VIOLENCE, POLVIOL_VIOLENCESTR

Question

How many guns do you or anyone else living here own?

Type the number.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable

Survey Question(s)

OWNGUN_GUNNUM

Variable Note

PAPI respondents received this question in the post-election interview. A pre-post summary variable has been created to summarize the responses from all modes.

Question

From which of the following sources have you heard anything about the presidential campaign?

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_CAMPSRCS

Question

From which of the following sources have you heard anything about the presidential campaign?

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_CAMPSRCS

Question

From which of the following sources have you heard anything about the presidential campaign?

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_CAMPSRCS

Question

From which of the following sources have you heard anything about the presidential campaign?

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_CAMPSRCS

Question

From which of the following sources have you heard anything about the presidential campaign?

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_CAMPSRCS

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS1

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS2

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following television programs do you watch regularly? Please check any that you watch at least once a month.

(Mark all that apply)

Value Labels

-9. Refused
-5. Break off, sufficient partial
-4. Error
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

MEDSRC_TVPROGS4

Universe

IF HEARD ABOUT PRES CAMPAIGN ON TV NEWS/TALK/PUBLIC AFFAIRS/ NEWS ANALYSIS PROG(S):
IF R IS HISPANIC:

Randomization

Order of TV show names across TVPROGS1, TVPROGS2, and TVPROGS4 (if applicable)

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following radio programs do you listen to regularly? Please check any that you listen to at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a technical error variables originating from the RADPROGS item will be released at a future date

Survey Question(s)

MEDSRC_RADPROGS

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON RADIO NEWS OR RADIO TALK PROGRAM(S):

Randomization

Order of radio program names

Response Order

Rand exc last

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following websites do you visit regularly? Please check any that you visit at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_WEBSITES

Universe

IF R HEARD ABOUT PRES CAMPAIGN ON INTERNET SITE(S), CHAT ROOM(S), OR BLOG(S):

Randomization

Order of website names

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following newspapers do you read online or in print regularly? Please check any that you read at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_INETNEWS

Universe

IF R HEARD ABOUT PRES CAMPAIGN IN NEWSPAPERS:

Randomization

Order of newspapers

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following newspapers do you read online or in print regularly? Please check any that you read at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_INETNEWS

Universe

IF R HEARD ABOUT PRES CAMPAIGN IN NEWSPAPERS:

Randomization

Order of newspapers

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following newspapers do you read online or in print regularly? Please check any that you read at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_INETNEWS

Universe

IF R HEARD ABOUT PRES CAMPAIGN IN NEWSPAPERS:

Randomization

Order of newspapers

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following newspapers do you read online or in print regularly? Please check any that you read at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_INETNEWS

Universe

IF R HEARD ABOUT PRES CAMPAIGN IN NEWSPAPERS:

Randomization

Order of newspapers

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following newspapers do you read online or in print regularly? Please check any that you read at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_INETNEWS

Universe

IF R HEARD ABOUT PRES CAMPAIGN IN NEWSPAPERS:

Randomization

Order of newspapers

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

Which of the following newspapers do you read online or in print regularly? Please check any that you read at least once a month.

(Mark all that apply)

Value Labels

-2. Due to a potential error variables originating from the WEBSITES/INETNEWS item have been temporarily removed

Survey Question(s)

MEDSRC_INETNEWS

Universe

IF R HEARD ABOUT PRES CAMPAIGN IN NEWSPAPERS:

Randomization

Order of newspapers

Response Order

Rand exc last

Variable Note

Data of this variable was removed in the full release version (20260519) of the 2024 Time Series data while under further investigation.

Question

‘Many women interpret innocent remarks or acts as being sexist.’

Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Agree strongly
2. Agree somewhat
3. Neither agree nor disagree
4. Disagree somewhat
5. Disagree strongly

Survey Question(s)

GENDRES_INNOCENT

Response Order

Forward/Reverse order

Question

‘Women seek to gain power by getting control over men.’

Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Agree strongly
2. Agree somewhat
3. Neither agree nor disagree
4. Disagree somewhat
5. Disagree strongly

Survey Question(s)

GENDRES_CONTROL

Response Order

Forward/Reverse order

Question

We are interested in the guesses people make when they do not know the answer to a question. We will ask you several questions. Some may be easy, but others are meant to be so difficult that you will have to guess.

In fact, for some of these questions, if you answer correctly, we will know that you probably looked up the answer.

Please do not look up the answers you do not know. Instead, please just make your best guess.

Will you please promise to try your best without looking up any answers? Or do you not want to make that promise?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. I promise to try my best without looking up any answers
2. I do not want to make that promise

Survey Question(s)

PREKNOW_COMMIT

Question

In what year did the Supreme Court of the United States decide Halstead v. Grinnan?

Type the year.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1894 (correct)

Survey Question(s)

PREKNOW_CATCH

Question

You are right! Did you look up the answer to that question, or did you already know it yourself?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. I looked it up
2. I already knew it

Survey Question(s)

PREKNOW_FEEDBACK1

Universe

IF R ANSWERED PREKNOW_CATCH CORRECTLY:

Question

For how many years is a United States Senator elected – that is, how many years are there in one full term of office for a U.S. Senator?

Type the number.

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable

Survey Question(s)

PREKNOW_SENTERM

Question

On which of the following does the U.S. federal government currently spend the least?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Foreign aid
2. Medicare
3. National defense
4. Social Security

Survey Question(s)

PREKNOW_LEASTSP

Randomization

Order of responses

Response Order

Randomized order

Question

Do you happen to know which party currently has the most members in the U.S. House of Representatives in Washington?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Democrats
2. Republicans

Survey Question(s)

PREKNOW_HSEMEM

Question

Do you happen to know which party currently has the most members in the U.S. Senate?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Democrats
2. Republicans

Survey Question(s)

PREKNOW_SENMEM

Question

People may encounter different mixes of political views in conversation. How about you? When you have political conversations with family, friends, neighbors and coworkers are the views you hear…

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Almost all liberal views
2. Mostly liberal but some conservative views
3. About an equal mix
4. Mostly conservative but some liberal views
5. Almost all conservative views
6. I don’t have conversations about politics

Survey Question(s)

GSSPRE_NETWORKPRE

Universe

IF R IS IN GSS SAMPLE:

Question

This interview is almost done. How would you rate the interviewer’s performance during the interview today?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Extremely good
2. Moderately good
3. A little good
4. Neither good nor bad
5. A little bad
6. Moderately bad
7. Extremely bad

Survey Question(s)

IW_IWRRATE

Universe

IF MODE IS FTF:

Response Order

Forward/Reverse order

Question

How would you rate this interview for the American National Election Studies?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Liked a great deal
2. Liked a moderate amount
3. Liked a little
4. Neither liked nor disliked
5. Disliked a little
6. Disliked a moderate amount
7. Disliked a great deal

Survey Question(s)

IW_RATE

Response Order

Forward/Reverse order

Question

We sometimes find people don’t always take surveys seriously,instead providing funny or insincere answers. How often did you give a serious response to the questions on this survey?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Never serious
2. Some of the time serious
3. About half of the time serious
4. Most of the time serious
5. Always serious

Survey Question(s)

IW_SERIOUS

Question

How easy was it for you to get access to a computer with an internet connection to take this survey? Was it [not at all easy, a little easy, moderately easy, very easy, or extremely easy / extremely easy, very easy, moderately easy, a little easy, or not at all easy]?

Value Labels

-9. Refused
-5. Break off, sufficient partial
-1. Inapplicable
1. Not at all easy
2. A little easy
3. Moderately easy
4. Very easy
5. Extremely easy

Survey Question(s)

IW_ONLINE

Universe

IF MODE IS WEB:

Response Order

Forward/Reverse order

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

All things considered, how satisfied are you with your life as a whole these days? Would you say that you are [extremely satisfied, very satisfied, moderately satisfied, slightly satisfied, or not satisfied at all / not satisfied at all, slightly satisfied, moderately satisfied, very satisfied, or extremely satisfied]?

Value Labels

-9. Refused
-8. Don’t know
-5. Break off, sufficient partial
-1. Inapplicable
1. Extremely satisfied
2. Very satisfied
3. Moderately satisfied
4. Slightly satisfied
5. Not satisfied at all

Survey Question(s)

HAPP_LIFESATISF

Response Order

Forward/Reverse order

Question

Please share any comments you have. We welcome your feedback.

Click Next to complete the survey.

Value Labels

-3. RESTRICTED

Survey Question(s)

ENDWEB_COMMT

Universe

IF MODE IS WEB:

Question

Enter number of campaign or political signs visible in the structure’s window(s) at the time the interview was completed.

Value Labels

-1. Inapplicable
99. Unknown

Survey Question(s)

IWROBSPRE_DU17

Universe

IF MODE IS FTF:

Question

Enter number of campaign or political signs in front/outside of the structure at the time the interview was completed.

Value Labels

-1. Inapplicable
99. Unknown

Survey Question(s)

IWROBSPRE_DU19

Universe

IF MODE IS FTF:

Question

Do any of the signs (in the window or outside the structure) support Joe Biden?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

IWROBSPRE_DU21

Universe

IF MODE IS FTF:
IF 1 OR MORE POLITICAL SIGNS IN STRUCTURE WINDOW AT THE TIME IW COMPLETED /
IF 1 OR MORE POLITICAL SIGNS OUTSIDE/IN FRONT OF STRUCTURE AT TIME IW COMPLETED:

Question

Do any of the signs (in the window or outside the structure) support ^dem_pcname (NOT including “Biden/Harris” signs)?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

IWROBSPRE_DU22

Universe

IF MODE IS FTF:
IF 1 OR MORE POLITICAL SIGNS IN STRUCTURE WINDOW AT THE TIME IW COMPLETED /
IF 1 OR MORE POLITICAL SIGNS OUTSIDE/IN FRONT OF STRUCTURE AT TIME IW COMPLETED:

Question

Do any of the signs (in the window or outside the structure) support ^rep_pcname?

Value Labels

-1. Inapplicable
1. Yes
2. No

Survey Question(s)

IWROBSPRE_DU23

Universe

IF MODE IS FTF:
IF 1 OR MORE POLITICAL SIGNS IN STRUCTURE WINDOW AT THE TIME IW COMPLETED /
IF 1 OR MORE POLITICAL SIGNS OUTSIDE/IN FRONT OF STRUCTURE AT TIME IW COMPLETED:

Question

Besides you and the respondent, who else was present during the interview?

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_OTHPRES

Universe

IF MODE IS FTF:

Question

Besides you and the respondent, who else was present during the interview?

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_OTHPRES

Universe

IF MODE IS FTF:

Question

Besides you and the respondent, who else was present during the interview?

Value Labels

-1. Inapplicable

Survey Question(s)

IWROBSPRE_OTHPRES

Universe

IF MODE IS FTF:

Question

Besides you and the respondent, who else was present during the interview?

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_OTHPRES

Universe

IF MODE IS FTF:

Question

Besides you and the respondent, who else was present during the interview?

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_OTHPRES

Universe

IF MODE IS FTF:

Question

Besides you and the respondent, who else was present during the interview?

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_OTHPRES

Universe

IF MODE IS FTF:

Question

Besides you and the respondent, who else was present during the interview?

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_OTHPRES

Universe

IF MODE IS FTF:

Question

R’s cooperation was:

Value Labels

-1. Inapplicable
1. Very good
2. Good
3. Fair
4. Poor
5. Very poor

Survey Question(s)

IWROBSPRE_COOP

Universe

IF MODE IS FTF:

Question

R’s general level of information about politics and public affairs seemed:

Value Labels

-1. Inapplicable
1. Very high
2. Fairly high
3. Average
4. Fairly low
5. Very low

Survey Question(s)

IWROBSPRE_LEVINF

Universe

IF MODE IS FTF:

Question

R’s apparent intelligence:

Value Labels

-1. Inapplicable
1. Very high
2. Fairly high
3. Average
4. Fairly low
5. Very low

Survey Question(s)

IWROBSPRE_INTELL

Universe

IF MODE IS FTF:

Question

How suspicious did R seem to be about the study before the interview?

Value Labels

-1. Inapplicable
1. Not at all suspicious
2. Somewhat suspicious
3. Very suspicious

Survey Question(s)

IWROBSPRE_SUSPIC

Universe

IF MODE IS FTF:

Question

Overall, how great was R’s interest in the interview?

Value Labels

-1. Inapplicable
1. Very high
2. Fairly high
3. Average
4. Fairly low
5. Very low

Survey Question(s)

IWROBSPRE_INTIW

Universe

IF MODE IS FTF:

Question

How honest did R seem to be in his or her answers?

Value Labels

-1. Inapplicable
1. Completely honest
2. Usually honest
3. Often seemed dishonest

Survey Question(s)

IWROBSPRE_HONEST

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPRE_REACT

Universe

IF MODE IS FTF:

Value Labels

-1. Inapplicable
1. Electronic
2. Paper

Value Labels

-1. Inapplicable
0. Not indicated
1. Yes, I am the named person

Survey Question(s)

SPS Q1

Value Labels

-9. Refused
-1. Inapplicable
1. Always
2. Most of the time
3. About half the time
4. Some of the time
5. Never

Survey Question(s)

SPS Q2

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Donald Trump (Republican)
2. Kamala Harris (Democrat)
3. Robert F. Kennedy (independent)
4. Cornel West (independent)
5. Jill Stein (Green)
6. Another candidate
7. No preference

Survey Question(s)

SPS Q3

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Strong
2. Not strong

Survey Question(s)

SPS Q4

Value Labels

-9. Refused
-1. Inapplicable
1. Donald Trump (Republican)
2. Kamala Harris (Democrat)
3. Would not vote

Survey Question(s)

SPS Q5

Value Labels

-9. Refused
-1. Inapplicable
1. I’ve already voted
2. Extremely likely
3. Very likely
4. Moderately likely
5. Slightly likely
6. Not likely at all

Survey Question(s)

SPS Q6

Value Labels

-9. Refused
-1. Inapplicable
1. Strong Democrat
2. Not very strong Democrat
3. independent leaning toward Democrat
4. independent
5. independent leaning toward Republican
6. Not very strong Republican
7. Strong Republican

Survey Question(s)

SPS Q7

Value Labels

-4. Error
-1. Inapplicable
0. Zero days
1. One day
2. Two days
3. Three days
4. Four days
5. Five days
6. Six days
7. Seven days

Survey Question(s)

SPS Q8

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Extremely liberal
2. Liberal
3. Slightly liberal
4. Moderate; middle of the road
5. Slightly conservative
6. Conservative
7. Extremely conservative

Survey Question(s)

SPS Q9

Value Labels

-9. Refused
-1. Inapplicable
1. Extremely worried
2. Very worried
3. Moderately worried
4. A little worried
5. Not at all worried

Survey Question(s)

SPS Q10

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Very satisfied
2. Fairly satisfied
3. Not very satisfied
4. Not at all satisfied

Survey Question(s)

SPS Q11

Value Labels

-4. Error
-1. Inapplicable

Survey Question(s)

SPS Q12

Value Labels

-9. Refused
-1. Inapplicable

Survey Question(s)

SPS Q13

Value Labels

-1. Inapplicable

Survey Question(s)

SPS Q14

Value Labels

-1. Inapplicable

Survey Question(s)

SPS Q15

Value Labels

-9. Refused
-1. Inapplicable

Survey Question(s)

SPS Q16

Value Labels

-9. Refused
-1. Inapplicable

Survey Question(s)

SPS Q17

Value Labels

-9. Refused
-1. Inapplicable

Survey Question(s)

SPS Q18

Value Labels

-9. Refused
-1. Inapplicable

Survey Question(s)

SPS Q19

Value Labels

-9. Refused
-1. Inapplicable

Survey Question(s)

SPS Q20

Value Labels

-9. Refused
-1. Inapplicable
1. Donald Trump
2. Kamala Harris
3. Another candidate
4. No preference

Survey Question(s)

SPS Q21

Value Labels

-9. Refused
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. A little important
5. Not important at all

Survey Question(s)

SPS Q22

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Protestant
2. Roman Catholic
3. Jewish
4. Muslim
5. Atheist
6. Agnostic
7. Something else
8. Nothing in particular

Survey Question(s)

SPS Q23

Value Labels

-3. RESTRICTED
-1. Inapplicable

Survey Question(s)

SPS Q23

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Never
2. A few times a year
3. Once or twice a month
4. Almost every week
5. Every week

Survey Question(s)

SPS Q24

Value Labels

-9. Refused
-1. Inapplicable
1. Agree strongly
2. Agree somewhat
3. Neither agree nor disagree
4. Disagree somewhat
5. Disagree strongly

Survey Question(s)

SPS Q25

Value Labels

-9. Refused
-1. Inapplicable
1. Agree strongly
2. Agree somewhat
3. Neither agree nor disagree
4. Disagree somewhat
5. Disagree strongly

Survey Question(s)

SPS Q26

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Many more advantages
2. Somewhat more advantages
3. Just a few more advantages
4. Equal advantages and disadvantages
5. Just a ew more disadvantages
6. Somewhat more advantages
7. Many more disadvantages

Survey Question(s)

SPS Q27

Value Labels

Survey Question(s)

SPS Q28

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Abortion should always be legal for any reason
7. Abortion should always be illegal with no exceptions

Survey Question(s)

SPS Q29

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. A little important
5. Not important at all

Survey Question(s)

SPS Q30

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

SPS Q31

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Independence
2. Respect for elders

Survey Question(s)

SPS Q32

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Curiosity
2. Good manners

Survey Question(s)

SPS Q33

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Obedience
2. Self-reliance

Survey Question(s)

SPS Q34

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Being considerate
2. Well behaved

Survey Question(s)

SPS Q35

Value Labels

-9. Refused
-1. Inapplicable
1. Always
2. Most of the time
3. About half the time
4. Some of the time
5. Never

Survey Question(s)

SPS Q36

Value Labels

-9. Refused
-1. Inapplicable
1. All
2. Most
3. About half
4. A few
5. None

Survey Question(s)

SPS Q37

Value Labels

-9. Refused
-1. Inapplicable
1. A good deal
2. Some
3. Not much

Survey Question(s)

SPS Q38

Value Labels

-9. Refused
-1. Inapplicable
1. Strongly favor
2. Somewhat favor
3. Neither favor nor oppose
4. Somewhat oppose
5. Strongly oppose

Survey Question(s)

SPS Q39

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Strongly favor
2. Somewhat favor
3. Neither favor nor oppose
4. Somewhat oppose
5. Strongly oppose

Survey Question(s)

SPS Q40

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Strongly favor
2. Somewhat favor
3. Neither favor nor oppose
4. Somewhat oppose
5. Strongly oppose

Survey Question(s)

SPS Q41

Value Labels

-9. Refused
-1. Inapplicable
1. Not at all
2. A little
3. A moderate amount
4. A lot
5. A great deal

Survey Question(s)

SPS Q42

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Already voted
2. Extremely likely
3. Very likely
4. Moderately likely
5. Slightly likely
6. Not likely at all

Survey Question(s)

SPS Q43

Value Labels

Survey Question(s)

SPS Q44

Value Labels

-2. Open-ended responses available in separate file
-1. Inapplicable

Survey Question(s)

SPS Q45

Value Labels

-9. Refused
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Left the same as it is now
4. Decreased a little
5. Decreased a lot

Survey Question(s)

SPS Q46

Value Labels

-9. Refused
-1. Inapplicable
1. Gotten much better
2. Gotten somewhat better
3. Stayed about the same
4. Gotten somewhat worse
5. Gotten much worse

Survey Question(s)

SPS Q47

Value Labels

-9. Refused
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

SPS Q48

Value Labels

-9. Refused
-4. Error
-1. Inapplicable
1. Donald Trump was the legitimate winner of 2020 presidential election
2. Joe Biden was the legitimate winner of 2020 presidential election

Survey Question(s)

SPS Q49

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SPS Q50

POST‐ELECTION SURVEY VARIABLES

Question

Would you like to complete this survey in English or Spanish?

¿Quisiera completar esta encuesta en inglés o español?

Value Labels

-7. Insufficient partial, interview deleted
’-6. No post interview
-1. Inapplicable
1. English / ingles
2. Spanish / espanol

Survey Question(s)

STARTPO_LANGUAGESELECTPO

Question

For some of the questions, I’ll share my screen and show you a card with all the answer categories listed. This will help you choose the best answer because you won’t have to try to remember all the choices as I read them. {SHARE SCREEN TO SHOW BOOKLET COVER PAGE}

Can you see the “ANES Participant Booklet” now?

Value Labels

-7. Insufficient partial, interview deleted
’-6. No post interview
-1. Inapplicable
1. R sees booklet on screen {TURN OFF SCREEN SHARING}
2. R does not see booklet on screen {TURN OFF SCREEN SHARING}

Survey Question(s)

BOOKLETPO_VIDEO

Universe

IF INTERVIEW TYPE IS VIDEO:

Question

As you know, the political parties try to talk to as many people as they can to get them to vote for their candidate. Has anyone from one of the political parties called you up or come around and talked to you about the 2024 campaign, or has no one from the political parties talked to you?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Someone from the political parties talked to me about the 2024 campaign
2. No one from the political parties talked to me about the 2024 campaign

Survey Question(s)

MOBILPO_PTYMOBREV

Question

Which party was that?

Value Labels

-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democrats
2. Republicans
3. Both {VOL} - FTF only
5. Other {SPECIFY}

Survey Question(s)

MOBILPO_WHPTYMOB

Universe

IF SOMEONE FROM POLITICAL PARTY CONTACTED R ABOUT CAMPAIGN:

Question

Which party was that?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

MOBILPO_WHPTYMOB

Universe

IF SOMEONE FROM POLITICAL PARTY CONTACTED R ABOUT CAMPAIGN:

Question

As you know, the political parties try to talk to as many people as they can to get them to vote for their candidate. Has anyone from one of the political parties come around and talked to you about the 2024 campaign, or has no one from the political parties talked to you? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Someone from the Democratic party
2. Someone from the Republican Party
3. Someone from another party
4. No one from a political party
5. PAPI respondent selected 1 & 2

Survey Question(s)

PAPI POST Q2

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-2. DK/RF in V242004, V242005, V242006
1. Someone from the Democratic party
2. Someone from the Republican Party
3. Someone from both Democratic & Republican Parties
4. Someone from another party
5. No one from any political party

Survey Question(s)

MOBILPO_PTYMOBREV, MOBILPO_WHPTYMOB, PAPI POST Q2

Question

Other than someone from the two major parties, did anyone (else) call you up or come around and talk to you about supporting specific candidates in this last election?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_OTHMOB

Question

During the campaign this year, did anyone talk to you about registering to vote or getting out to vote?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, someone did
2. No, no one did

Survey Question(s)

MOBILPO_MOBREG, PAPI POST Q3

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

We would like to find out about some of the things people do to help a party or a candidate win an election. During the campaign, did you talk to any people and try to show them why they should vote for or against one of the parties or candidates?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_RMOB, PAPI POST Q4

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Did you participate in any online political meetings, rallies, speeches, fundraisers, or things like that in support of a particular candidate?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_RRALLYONLINE

Question

Did you go to any political meetings, rallies, speeches, dinners, or things like that in support of a particular candidate?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_RRALLY, PAPI POST Q5

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Did you wear a campaign button, put a campaign sticker on your car, or place a sign in your window or in front of your house?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_RBUTTN, PAPI POST Q6

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Did you do any (other) work for one of the parties or candidates?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_RCAMPWK, PAPI POST Q7

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

During an election year people are often asked to make a contribution to support campaigns. Did you give money to an individual candidate running for public office in this year’s election?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, one candidate
2. Yes, more than one candidate
3. No candidates

Survey Question(s)

MOBILPO_CTBCAND

Question

Which party did that candidate belong to?

Value Labels

-3. RESTRICTED

Survey Question(s)

MOBILPO_CTBCANDPTYONE

Universe

IF R DONATED TO ONE CANDIDATE:

Question

Which party did that candidate belong to?

Value Labels

-3. RESTRICTED

Survey Question(s)

MOBILPO_CTBCANDPTYONE

Universe

IF R DONATED TO ONE CANDIDATE:

Question

Which party or parties did those candidates belong to?

Value Labels

-3. RESTRICTED

Survey Question(s)

MOBILPO_CTBCNDPTYMULT

Universe

IF R DONATED TO MORE THAN ONE CANDIDATE:

Question

Which party or parties did those candidates belong to?

Value Labels

-3. RESTRICTED

Survey Question(s)

MOBILPO_CTBCNDPTYMULT

Universe

IF R DONATED TO MORE THAN ONE CANDIDATE:

Question

During an election year people are often asked to make contributions to support campaigns. Did you give money to an individual candidate running for public office? Mark all that apply.

Value Labels

-3. RESTRICTED

Survey Question(s)

PAPI POST Q8

Value Labels

-3. RESTRICTED

Question

Did you give money to a political party during this election year?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_CTBPTY

Question

To which party did you give money?

Value Labels

-3. RESTRICTED

Survey Question(s)

MOBILPO_CTBWHPTY

Universe

IF R CONTRIBUTED MONEY TO POLITICAL PARTY:

Question

To which party did you give money?

Value Labels

-3. RESTRICTED

Survey Question(s)

MOBILPO_CTBWHPTY

Universe

IF R CONTRIBUTED MONEY TO POLITICAL PARTY:

Question

To which political party did you give money this election year, or did you not give money? Mark all that apply.

Value Labels

-3. RESTRICTED

Survey Question(s)

PAPI POST Q9

Value Labels

-3. RESTRICTED

Question

Did you give any money to any other group that supported or opposed candidates?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

MOBILPO_CTBOTH

Question

How many days in the past week did you talk about politics with family or friends?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-4. Error
-1. Inapplicable
0. Zero days
1. One day
2. Two days
3. Three days
4. Four days
5. Five days
6. Six days
7. Seven days

Survey Question(s)

DISCUSS_DISCPSTWK, PAPI POST Q10

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

How often do you discuss race or racial issues with children or teenagers in your household?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. All the time
2. Often
3. Sometimes
4. Rarely
5. Never

Survey Question(s)

DISCUSS_CHILDRACE

Universe

IF R HAS CHILDREN 17 OR YOUNGER IN PRE:

Question

How often do you discuss government and politics with children or teenagers in your household?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. All the time
2. Often
3. Sometimes
4. Rarely
5. Never

Survey Question(s)

DISCUSS_CHILDPOL

Universe

IF R HAS CHILDREN 17 OR YOUNGER IN PRE:

Question

How often, if at all, do you talk to friends or family who live in other countries about events happening in that country?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Never
2. Rarely
3. Occasionally
4. Somewhat often
5. Very often

Survey Question(s)

DISCUSS_INTLDISC

Question

During the past 12 months, have you joined in a protest march, rally, or demonstration, or have you not done this in the past 12 months?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Have done this in past 12 months
2. Have not done this in the past 12 months

Survey Question(s)

INVOLV_EVERRALLY, PAPI POST Q108_1

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

During the past 12 months, have you signed a petition on the Internet or on paper about a political or social issue, or have you not done this in the past 12 months?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Have done this in past 12 months
2. Have not done this in the past 12 months

Survey Question(s)

INVOLV_EVERSGNPET, PAPI POST Q108_2

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Not counting a religious organization, during the past 12 months, have you given money to any other organization concerned with a political or social issue, or have you not done this in the past 12 months?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Have done this in past 12 months
2. Have not done this in the past 12 months

Survey Question(s)

INVOLV_EVERGIVSOC

Question

During the past 12 months, have you posted a message or comment online about a political issue or campaign, or have you not done this in the past 12 months?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Have done this in past 12 months
2. Have not done this in the past 12 months

Survey Question(s)

INVOLV_EVERPOSTINT, PAPI POST Q108_3

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

During the past 12 months, have you ever gotten into a political argument with someone, or have you not done this in the past 12 months?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Have done this in past 12 months
2. Have not done this in the past 12 months

Survey Question(s)

INVOLV_EVERPOLARG, PAPI POST Q108_4

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

In the past 12 months, did you attend a public meeting, such as a zoning or school board meeting, to discuss a local issue?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

INVOLV_LCOMMMTGCPS

Question

In the past 12 months, did you spend any time volunteering for any organization or association?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

INVOLV_VOLTRCPS

Question

In the past twelve months, have you contacted a federal elected official, such as a member of Congress or the President, or someone on the staff of such an official? Please don’t count any contact you made as a regular part of your job.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, have done this in the past 12 months
2. No, have not done this

Survey Question(s)

INVOLV_CONTFEDEL

Question

In the past 12 months, did you buy or boycott products or services based on the political values or business practices of that company?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-4. Error
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

BUYCOTT_SOCPOL, PAPI POST Q13

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democrat / Republican
2. Republican / Democrat

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
0. Sample address not preloaded
1. Sample address preloaded

Question

Now on a different topic. Are you registered to vote?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

POSTVOTE_REGSTATUS, PAPI POST Q11

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF R WAS NOT REGISTERED IN THE PRE SURVEY:
IF R’S NEW STATE OF RESIDENCE IS NOT NORTH DAKOTA:

Question

[Now on a different topic. When did you register to vote for the first time? / When did you register to vote for the first time?] In the past twelve months, 1-2 years ago, 3-4 years ago, or 5 or more years ago?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. In the past twelve months
2. 1-2 years ago
3. 3-4 years ago
4. 5 or more years ago

Survey Question(s)

POSTVOTE_WHENREG

Universe

IF R IS REGISTERED TO VOTE:

Question

When did you register to vote for the first time, or have you never registered to vote?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Have never registered to vote
2. In the past twelve months
3. 1-2 years ago
4. 3-4 years ago
5. 5 or more years ago

Survey Question(s)

PAPI POST Q12

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Have never registered to vote
2. In the past twelve months
3. 1-2 years ago
4. 3-4 years ago
5. 5 or more years ago

Survey Question(s)

POSTVOTE_REGSTATUS, POSTVOTE_WHENREG, PAPI POST Q12

Question

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, this is the correct address
2. No, this is not the correct address

Survey Question(s)

POSTVOTE_ADDR

Question

What is the address you use for voting?

Value Labels

-3. RESTRICTED [STAFF ONLY]

Survey Question(s)

POSTVOTE_NEWADDR

Universe

IF PRELOAD ADDRESS IS NOT THE ADDRESS FOR VOTING:

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
0. Registration address not given
1. Registration address given

Survey Question(s)

POSTVOTE_NEWADDR

Question

It appears that the state name is missing from the address you provided. In what state is your address for voting?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Alabama  2. Alaska  4. Arizona
5. Arkansas  6. California  8. Colorado
9. Connecticut  10. Delaware
11. District of Columbia (Washington DC)
12. Florida  13. Georgia   15. Hawaii
16. Idaho   17. Illinois   18. Indiana
19. Iowa   20. Kansas   21. Kentucky
22. Louisiana   23. Maine   24. Maryland
25. Massachusetts   26. Michigan   27. Minnesota
28. Mississippi   29. Missouri   30. Montana
31. Nebraska   32. Nevada   33. New Hampshire
34. New Jersey   35. New Mexico   36. New York
37. North Carolina   38. North Dakota   39. Ohio
40. Oklahoma   41. Oregon   42. Pennsylvania
44. Rhode Island   45. South Carolina   46. South Dakota
47. Tennessee   48. Texas   49. Utah
50. Vermont   51. Virginia   53. Washington
54. West Virginia   55. Wisconsin   56. Wyoming

Survey Question(s)

POSTVOTE_NEWWHST

Universe

IF R DID NOT PROVIDE STATE NAME WHEN ASKED FOR NEW ADDRESS:

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
0. State of registration not the same as state of sample address
1. State of registration same as state of sample address

Value Labels

-1. Inapplicable
0. No Senate race in state of registration
1. Senate race in state of registration

Value Labels

-1. Inapplicable
0. No Governor race in state of registration
1. Governor race in state of registration

Value Labels

-1. Inapplicable
0. No party registration in state of registration
1. Party registration in state of registration

Question

How many years have you been registered to vote at [this/that] address?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable

Survey Question(s)

POSTVOTE_REGYRS

Universe

IF R SAID REGISTERED IN THE POST SURVEY:

Question

Value Labels

-3. RESTRICTED

Survey Question(s)

POSTVOTE_REGNAME

Universe

IF R INDICATED REGISTERED TO VOTE IN THE POST SURVEY:

Question

What political party are you registered with, if any?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic party
2. Republican party
4. None or ‘independent’
5. Other party {SPECIFY}

Survey Question(s)

POSTVOTE_REGPTY

Universe

IF R INDICATED REGISTERED TO VOTE IN THE POST SURVEY:
IF R IS REGISTERED TO VOTE IN STATE WHERE PARTY MAY BE REGISTERED:

Question

What political party are you registered with, if any?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_REGPTY

Universe

IF R INDICATED REGISTERED TO VOTE IN THE POST SURVEY:
IF R IS REGISTERED TO VOTE IN STATE WHERE PARTY MAY BE REGISTERED:

Question

In talking to people about elections, we often find that a lot of people were not able to vote because they weren’t registered, they were sick, or they just didn’t have time. Which of the following statements best describes you: One, I did not vote (in the election this November); Two, I thought about voting this time, but didn’t; Three, I usually vote, but didn’t this time; or Four, I am sure I voted?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. I did not vote (in the election this November)
2. I thought about voting this time, but didn’t
3. I usually vote, but didn’t this time
4. I am sure I voted

Survey Question(s)

POSTVOTE_RVOTE, PAPI POST Q14

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF R DID NOT REPORT IN THE PRE THAT R ALREADY VOTED:

Question

How about the election for President? Did you vote for a candidate for President?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, voted for President
2. No, didn’t vote for President

Survey Question(s)

POSTVOTE_PRESVT

Universe

IF R REPORTED IN THE POST SURVEY THAT R VOTED:

Question

Who did you vote for? [ Kamala Harris (Democrat), Donald Trump (Republican) / Donald Trump (Republican), Kamala Harris (Democrat)], Cornel West (Independent), Jill Stein (Green), or someone else?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Kamala Harris
2. Donald Trump
4. Cornel West
5. Jill Stein
6. Another candidate {SPECIFY}

Survey Question(s)

POSTVOTE_PRESVTWHO

Universe

IF R REPORTED IN THE POST THAT R VOTED FOR PRESIDENT:

Randomization

Order of Democratic Pres cand and Republican Pres cand names, according to candidateorder assigned in Pre (other response options in fixed order 3rd, 4th, 5th positions)

Response Order

Randomize 2 major parties

Question

Who did you vote for? [ Kamala Harris (Democrat), Donald Trump (Republican) / Donald Trump (Republican), Kamala Harris (Democrat)], Cornel West (Independent), Jill Stein (Green), or someone else?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_PRESVTWHO

Universe

IF R REPORTED IN THE POST THAT R VOTED FOR PRESIDENT:

Randomization

Order of Democratic Pres cand and Republican Pres cand names, according to candidateorder assigned in Pre (other response options in fixed order 3rd, 4th, 5th positions)

Response Order

Randomize 2 major parties

Question

How about the election for President? Who did you vote for, or did you not vote for President?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-4. Error
-1. Inapplicable
1. Didn’t vote for President
2. Donald Trump
3. Kamala Harris
4. Robert F. Kennedy, Jr.
5. Cornel West
6. Jill Stein
7. Other

Survey Question(s)

PAPI POST Q15

Question

Would you say your preference for this candidate was strong or not strong?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Strong
2. Not strong

Survey Question(s)

POSTVOTE_PRESSTR

Universe

IF R ANSWERED WHICH PRESIDENTIAL CANDIDATE THEY VOTED FOR:

Question

How long before Election day did you decide that you were going to vote the way you did?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. 0-2 weeks
2. 3-4 weeks
3. 2 months
4. 3 months
5. 4 months
6. 5 months
7. 6+ months

Survey Question(s)

POSTVOTE_VTPRESDEC

Universe

IF R ANSWERED WHICH PRESIDENTIAL CANDIDATE THEY VOTED FOR:

Question

Did you prefer one of the candidates in the November election for President?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

POSTVOTE_PREFPRES

Universe

IF R DID NOT REPORT IN THE POST SURVEY THAT R VOTED:

Question

Who did you prefer? [ Kamala Harris (Democrat), Donald Trump (Republican) / Donald Trump (Republican), Kamala Harris (Democrat)], Cornel West (Independent), Jill Stein (Green), or someone else?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Kamala Harris
2. Donald Trump
4. Cornel West
5. Jill Stein
6. Another candidate {SPECIFY}

Survey Question(s)

POSTVOTE_PREFPRWHO

Universe

IF R DID NOT VOTE BUT PREFERRED A PRESIDENTIAL CANDIDATE:

Randomization

Order of Democratic Pres cand and Republican Pres cand names, according to candidateorder assigned in Pre (other response options in fixed order 3rd, 4th, 5th positions)

Response Order

Randomize 2 major parties

Question

Who did you prefer? [ Kamala Harris (Democrat), Donald Trump (Republican) / Donald Trump (Republican), Kamala Harris (Democrat)], Cornel West (Independent), Jill Stein (Green), or someone else?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_PREFPRWHO

Universe

IF R DID NOT VOTE BUT PREFERRED A PRESIDENTIAL CANDIDATE:

Randomization

Order of Democratic Pres cand and Republican Pres cand names, according to candidateorder assigned in Pre (other response options in fixed order 3rd, 4th, 5th positions)

Response Order

Randomize 2 major parties

Question

Would you say your preference for this candidate was strong or not strong?

Value Labels

-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Strong
2. Not strong

Survey Question(s)

POSTVOTE_PREFPRSTR

Universe

IF R ANSWERED WHICH PRESIDENTIAL CANDIDATE THEY PREFERRED:

Question

How about the election for the House of Representatives in Washington. Did you vote for a candidate for the U.S. House of Representatives?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, voted for House of Representatives
2. No, didn’t vote for House of Representatives

Survey Question(s)

POSTVOTE_VOTEHS

Universe

IF R REPORTED IN THE POST SURVEY THAT R VOTED:

Question

What is the party of the House candidate you voted for?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic Party
2. Republican Party
5. Another party {SPECIFY}

Survey Question(s)

POSTVOTE_HSVTWHO

Universe

IF R SAID IN THE POST SURVEY THAT THEY VOTED FOR U.S. HOUSE OF REPRESENTATIVES:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

What is the party of the House candidate you voted for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_HSVTWHO

Universe

IF R SAID IN THE POST SURVEY THAT THEY VOTED FOR U.S. HOUSE OF REPRESENTATIVES:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you vote for in the election for the U.S. House of Representatives, or did you not vote?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-4. Error
-1. Inapplicable
1. Didn’t vote for US House of Representatives
2. Democratic party candidate
3. Republican party candidate
4. Other

Survey Question(s)

PAPI POST Q16

Question

How about the election for the House of Representatives in Washington? Did you prefer one of the candidates for the U.S. House of Representatives?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

POSTVOTE_HSPREF

Universe

IF R DID NOT REPORT IN THE POST SURVEY THAT R VOTED:

Question

What is the party of the House candidate you preferred?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic Party
2. Republican Party
5. Another party {SPECIFY}

Survey Question(s)

POSTVOTE_HSPREFWHO

Universe

IF R DID NOT VOTE BUT PREFERRED A CANDIDATE FOR U.S. HOUSE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

What is the party of the House candidate you preferred?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_HSPREFWHO

Universe

IF R DID NOT VOTE BUT PREFERRED A CANDIDATE FOR U.S. HOUSE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for the United States Senate? Did you vote for a candidate for the U.S. Senate?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, voted for Senate
2. No, didn’t vote for Senate

Survey Question(s)

POSTVOTE_VOTESEN

Universe

IF R REPORTED IN THE POST SURVEY THAT R VOTED:
IF A SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who did you vote for?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent candidate
5. Another candidate {SPECIFY}

Survey Question(s)

POSTVOTE_VTSENWHO

Universe

IF R VOTED FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_VTSENWHO

Universe

IF R VOTED FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for the United States Senate? Did you prefer one of the candidates for the U.S. Senate?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

POSTVOTE_SENPREF

Universe

IF R DID NOT REPORT IN THE POST SURVEY THAT R VOTED:
IF A SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who did you prefer?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent candidate
5. Another candidate {SPECIFY}

Survey Question(s)

POSTVOTE_SENPREFWHO

Universe

IF R DID NOT VOTE BUT PREFERS A CANDIDATE FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you prefer?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_SENPREFWHO

Universe

IF R DID NOT VOTE BUT PREFERS A CANDIDATE FOR U.S. SENATE:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the special election for the United States Senate seat now held by the Republican Pete Ricketts? Did you vote for a candidate for the U.S. Senate?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, voted for Senate
2. No, didn’t vote for Senate

Survey Question(s)

POSTVOTE_VOTESEN2

Universe

IF R REPORTED IN THE POST SURVEY THAT R VOTED:
IF A SPECIAL SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who did you vote for?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic Senate candidate
2. Republican Senate candidate
3. Independent Senate candidate
5. Another candidate {SPECIFY}

Survey Question(s)

POSTVOTE_VTSEN2WHO

Universe

IF R VOTED FOR U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_VTSEN2WHO

Universe

IF R VOTED FOR U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the special election for the United States Senate seat now held by the Republican Pete Ricketts? Did you prefer one of the candidates for the U.S. Senate?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

POSTVOTE_SENPREF2

Universe

IF R DID NOT REPORT IN THE POST SURVEY THAT R VOTED:
IF A SPECIAL SENATE RACE WAS HELD IN REGISTRATION STATE:

Question

Who did you prefer?

Value Labels

Survey Question(s)

POSTVOTE_SENPREF2WHO

Universe

IF R DID NOT VOTE BUT PREFERS A CANDIDATE FOR U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you prefer?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_SENPREF2WHO

Universe

IF R DID NOT VOTE BUT PREFERS A CANDIDATE FOR U.S. SPECIAL SENATE ELECTION:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for Governor? Did you vote for a candidate for Governor?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes, voted for governor
2. No, didn’t vote for governor

Survey Question(s)

POSTVOTE_VOTEGOV

Universe

IF R REPORTED IN THE POST SURVEY THAT R VOTED:
IF A GUBERNATORIAL RACE WAS HELD IN REGISTRATION STATE:

Question

Who did you vote for?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic Gubernatorial candidate
2. Republican Gubernatorial candidate
3. Independent Gubernatorial candidate
5. Another candidate {SPECIFY}

Survey Question(s)

POSTVOTE_VTGOVWHO

Universe

IF R VOTED FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you vote for?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_VTGOVWHO

Universe

IF R VOTED FOR GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

How about the election for Governor? Did you prefer one of the candidates for Governor?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

POSTVOTE_GOVPREF

Universe

IF R DID NOT REPORT IN THE POST SURVEY THAT R VOTED:
IF A GUBERNATORIAL RACE WAS HELD IN STATE OF RESIDENCE:

Question

Who did you prefer?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. Democratic Gubernatorial candidate
2. Republican Gubernatorial candidate
3. Independent Gubernatorial candidate
5. Another candidate {SPECIFY}

Survey Question(s)

POSTVOTE_GOVPREFWHO

Universe

IF R DID NOT VOTE BUT PREFERS A CANDIDATE FOR R GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Question

Who did you prefer?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

POSTVOTE_GOVPREFWHO

Universe

IF R DID NOT VOTE BUT PREFERS A CANDIDATE FOR R GOVERNOR:

Randomization

Order of response options 1-2 according to value in var candidateorder.

Response Order

Randomize 2 major parties

Value Labels

-1. Inapplicable
-7. Insufficient partial, interview deleted
-6. No post interview
-2. Missing, no post vote/preference data: DK/RF/INAP
10. Democratic candidate selected (vote)
11. Republican candidate selected (vote)
12. Other candidate selected (vote)
30. Democratic candidate selected (preference; nonvoter)
31. Republican candidate selected (preference; nonvoter)
32. Other candidate selected (preference; nonvoter)

Survey Question(s)

POSTVOTE_PRESVTWHO, POSTVOTE_PREFPRWHO, PAPI POST Q15

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-2. Missing, no post vote/preference data: DK/RF/INAP
10. Democratic candidate selected (vote)
11. Republican candidate selected (vote)
12. Other candidate selected (vote)
30. Democratic candidate selected (preference; nonvoter)
31. Republican candidate selected (preference; nonvoter)
32. Other candidate selected (preference; nonvoter)

Survey Question(s)

POSTVOTE_HSVTWHO,POSTVOTE_ HSPREFWHO

Value Labels

Survey Question(s)

POSTVOTE_VTSENWHO, POSTVOTE_SENPREFWHO

Value Labels

Survey Question(s)

POSTVOTE_VTGOVWHO, POSTVOTE_GOVPREFWHO

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-2. Not reported
0. Did not vote
1. Voted

Survey Question(s)

PREVOTE_VCONF, POSTVOTE_RVOTE, PAPI POST Q14

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-2. Missing, no pre/post vote data: DK/RF/INAP
1. Kamala Harris
2. Donald Trump
3. Robert F. Kennedy, Jr
4. Cornel West
5. Jill Stein
6. Other

Survey Question(s)

PREVOTE_PRESVTWHO, POSTVOTE_PRESVTWHO, PAPI POST Q15

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-2. Missing, no pre/post vote data: DK/RF/INAP
1. Voted for Democratic candidate
2. Voted for Republican candidate
3. Voted for other candidate

Survey Question(s)

PREVOTE_HSVTWHO, POSTVOTE_HSVTWHO, PAPI POST Q16

Value Labels

Survey Question(s)

PREVOTE_VTSENWHO, POSTVOTE_VTSENWHO

Value Labels

Survey Question(s)

PREVOTE_VTGOVWHO, POSTVOTE_VTGOVWHO

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

What is the main reason you are not registered to vote?

You can just give me the number or numbers of your choices.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

NONREG_REASON

Universe

IF R IS NOT REGISTERED TO VOTE:

Question

You said there were other reasons you are not registered to vote. What are those reasons?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

NONREG_OTHREASON

Universe

IF REASON R IS NOT REGISTERED WAS GIVEN AS ‘OTHER’:

Question

When did you cast your vote in the 2024 general election? On election day, a few days before the election day, or a week or more before the election day?

Value Labels

-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. On election day
2. A few days before election day
3. A week or more before election day

Survey Question(s)

VOTEEXP_WHENVOTE

Universe

IF R VOTED:

Question

Did you vote on election day, before election day, or did you not vote?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. On election day (Tuesday, November 5)
2. Before election day
3. I did not vote

Survey Question(s)

PAPI POST Q18

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. On election day
2. Before election day
3. Did not vote

Survey Question(s)

POSTVOTE_RVOTE, VOTEEXP_WHENVOTE, PAPI POST Q18

Question

How did you vote? In person at the polling place, or by mail or absentee ballot?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. In person, at the polling place
2. By mail or absentee ballot

Survey Question(s)

VOTEEXP_HOWVOTE

Universe

IF R VOTED:

Question

How did you vote? In person at the polling place, by mail or absentee ballot, or did you not vote?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. In person, at polling place
2. By mail or absentee ballot
3. I did not vote

Survey Question(s)

PAPI POST Q17

Value Labels

Survey Question(s)

POSTVOTE_RVOTE, VOTEEXP_HOWVOTE, PAPI POST Q17

Question

Thinking back to previous elections, how do you usually vote? In-person at the polling place, by mail or absentee ballot, or is this your first time voting?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. In-person, at the polling place
2. By mail or absentee ballot
3. This is my first time voting

Survey Question(s)

VOTEEXP_USUALVOTE

Universe

IF R VOTED:

Question

Thinking back to previous elections, how do you usually vote? In person at the polling place, by mail or absentee ballot, is this your first time voting, or have you never voted?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. In-person, at the polling place
2. By mail or absentee ballot
3. This is my first time voting
4. I have never voted

Survey Question(s)

PAPI POST Q19

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. In-person, at the polling place
2. By mail or absentee ballot
3. This is my first time voting
4. I have never voted

Survey Question(s)

POSTVOTE_RVOTE, VOTEEXP_USUALVOTE, PAPI POST Q19

Question

How difficult was it for you to vote in this election? [Not difficult at all, a little difficult, moderately difficult, very difficult, or extremely difficult / Extremely difficult, very difficult, moderately difficult, a little difficult, or not difficult at all]?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not difficult at all
2. A little difficult
3. Moderately difficult
4. Very difficult
5. Extremely difficult

Survey Question(s)

VOTEEXP_VOTEHARD

Universe

IF R VOTED:

Response Order

Forward/Reverse order

Question

How difficult was it for you to vote in this election, or did you not vote?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Not difficult at all
2. A little difficult
3. Moderately difficult
4. Very difficult
5. Extremely difficult
6. Did not vote

Survey Question(s)

PAPI POST Q20

Value Labels

Survey Question(s)

POSTVOTE_RVOTE, VOTEEXP_VOTEHARD, PAPI POST Q20

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

Did you encounter any of the following problems in trying to vote in this election?

(MARK ALL THAT APPLY.)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

VOTEEXP_VOTEPROB

Question

About how long was the wait time at your polling place?

0-15 minutes, 16-30 minutes, 31-59 minutes, 1-2 hours, or more than 2 hours?

Value Labels

-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. 0-15 minutes
2. 16-30 minutes
3. 31-59 minutes
4. 1-2 hours
5. More than 2 hours

Survey Question(s)

VOTEEXP_WAITTIME

Universe

IF R VOTED IN-PERSON:

Question

About how long does it take you to travel to your polling place?

0-15 minutes, 16-30 minutes, 31-59 minutes, 1-2 hours, or more than 2 hours?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. 0-15 minutes
2. 16-30 minutes
3. 31-59 minutes
4. 1-2 hours
5. More than 2 hours

Survey Question(s)

VOTEEXP_TRVLTIME

Universe

IF R VOTED IN-PERSON:

Question

Now we have a set of questions concerning various public figures.

We are interested in the guesses people make when they do not know the answer to a question. We will ask you about several public figures. Some may be easy, but others are meant to be so difficult that you will have to guess.

In fact, for some of these questions, if you answer correctly, we will know that you probably looked up the answer.

Please do not look up the answers you do not know. Instead, please just make your best guess.

Will you please promise to try your best without looking up any answers? Or do you not want to make that promise?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. I promise to do my best without looking up any answers
2. I do not want to make that promise

Survey Question(s)

OFCREC_COMMIT, PAPI POST Q24

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

The first name is: Lemanu Peleti Mauga What job or political office does he now hold?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

OFCREC_CATCH

Universe

IF TYPE=WEB:

Question

The first name is: Lemanu Peleti Mauga What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Partially correct
2. Correct

Survey Question(s)

OFCREC_CATCH

Universe

IF TYPE=WEB:

Question

You are right! Did you look up the answer to that question, or did you already know it yourself?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. I looked it up
2. I already knew it

Survey Question(s)

OFCREC_FEEDBACK1

Universe

IF TYPE=WEB /
IF CATCH ANSWERED CORRECTLY = RESPONSE INCLUDES “SAMOA” OR “GOV”:

Question

The first name is: Chuck Schumer

What job or political office does he now hold?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

OFCREC_KNMAJ, PAPI POST Q28

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

The first name is: Chuck Schumer

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Partially correct
2. Correct

Survey Question(s)

OFCREC_KNMAJ, PAPI POST Q28

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

The first name is: Chuck Schumer

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Correct

Survey Question(s)

OFCREC_KNMAJ, PAPI POST Q28

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Mike Johnson

What job or political office does he now hold?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

OFCREC_KNSPK, PAPI POST Q27

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Mike Johnson

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Correct

Survey Question(s)

OFCREC_KNSPK, PAPI POST Q27

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Mike Johnson

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Partially correct
2. Correct

Survey Question(s)

OFCREC_KNSPK, PAPI POST Q27

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Emmanuel Macron

What job or political office does he now hold?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

OFCREC_KNFRPR, PAPI POST Q29

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Emmanuel Macron

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Correct

Survey Question(s)

OFCREC_KNFRPR, PAPI POST Q29

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Two coding schemes were used to code responses to OFCREC_KNFRPR. Scheme 1 was a more generous coding scheme giving while scheme 2 was more stringent in designating correct answers.

Question

Emmanuel Macron

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Correct

Survey Question(s)

OFCREC_KNFRPR, PAPI POST Q29

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Two coding schemes were used to code responses to OFCREC_KNFRPR. Scheme 1 was a more generous coding scheme giving while scheme 2 was more stringent in designating correct answers.

Question

Vladimir Putin

What job or political office does he now hold?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

OFCREC_KNRUS, PAPI POST Q26

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Vladimir Putin

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Correct

Survey Question(s)

OFCREC_KNRUS, PAPI POST Q26

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Two coding schemes were used to code responses to OFCREC_KNRUS. Scheme 1 was a more generous coding scheme giving while scheme 2 was more stringent in designating correct answers.

Question

Vladimir Putin

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Correct

Survey Question(s)

OFCREC_KNRUS, PAPI POST Q26

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Two coding schemes were used to code responses to OFCREC_KNRUS. Scheme 1 was a more generous coding scheme giving while scheme 2 was more stringent in designating correct answers.

Question

John Roberts

What job or political office does he now hold?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

OFCREC_KNCHJ, PAPI POST Q25

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

John Roberts

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Partially correct
2. Correct

Survey Question(s)

OFCREC_KNCHJ, PAPI POST Q25

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

John Roberts

What job or political office does he now hold?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing
-1. Inapplicable
0. Incorrect
1. Correct

Survey Question(s)

OFCREC_KNCHJ, PAPI POST Q25

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

How would you rate: Kamala Harris

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPODPC, PAPI POST Q32

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Democratic and Republican Presidential candidate thermometers

Question

How would you rate: Donald Trump

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPORPC, PAPI POST Q31

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of Democratic and Republican Presidential candidate thermometers

Question

(How would you rate:) The [Democratic/Republican] candidate for House of Representatives that you voted for?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPOHSCANDVT

Universe

IF R VOTED FOR HOUSE OF REPRESENTATIVES IN PRE-ELECTION STUDY /
IF R VOTED FOR HOUSE OF REPRESENTATIVES IN POST-ELECTION STUDY:

Question

(How would you rate:) The Democratic candidate for House of Representatives in your district?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPOHSDCAND

Universe

IF R VOTED FOR HOUSE OF REPRESENTATIVES IN PRE-ELECTION STUDY /
IF R VOTED FOR HOUSE OF REPRESENTATIVES IN POST-ELECTION STUDY /
IF R VOTE FOR A REPUBLICAN OR OTHER/3RD PARTY CANDIDATE IN HOUSE ELECTION:

Randomization

IF HSVTWHO = 5, randomize order of THPOHSDCAND and THPOHSRCAND.

Question

(How would you rate:) The Republican candidate for House of Representatives in your district?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPOHSRCAND

Universe

IF R VOTED FOR HOUSE OF REPRESENTATIVES IN PRE-ELECTION STUDY /
IF R VOTED FOR HOUSE OF REPRESENTATIVES IN POST-ELECTION STUDY /
IF R VOTE FOR A DEMOCRATIC OR OTHER/3RD PARTY CANDIDATE IN HOUSE ELECTION:

Randomization

IF PREVOTE_HSVTWHO = 5 or POSTVOTE_HSVTWHO = 5, randomize order of THPOHSDCAND and THPOHSRCAND.

Question

(How would you rate:) [Name of Democratic candidate in Senate election in R’s state]

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPOSDC

Universe

IF SENATE RACE IN R’S CURRENT STATE:
IF DEMOCRATIC CANDIDATE IN SENATE RACE:

Randomization

Order of thermometer names after major party Presidential candidate thermometers

Question

(How would you rate:) [Name of Republican candidate in Senate election in R’s state]

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPOSRC

Universe

IF SENATE RACE IN R’S CURRENT STATE:
IF REPUBLICAN CANDIDATE IN SENATE RACE:

Randomization

Order of thermometer names after major party Presidential candidate thermometers

Question

(How would you rate:) [Name of Democratic candidate in Senate special election in R’s state]

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPOSSDC

Universe

IF SPECICAL SENATE RACE IN R’S CURRENT STATE:
IF DEMOCRATIC CANDIDATE IN SPECIAL SENATE RACE:

Randomization

Order of thermometer names after major party Presidential candidate thermometers

Question

(How would you rate:) [Name of Republican candidate in Senate special election in R’s state]

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPOSSRC

Universe

IF SPECIAL SENATE RACE IN R’S CURRENT STATE:
IF REPUBLICAN CANDIDATE IN SPECIAL SENATE RACE:

Randomization

Order of thermometer names after major party Presidential candidate thermometers

Question

(How would you rate:) Tim Walz

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPODVPC, PAPI POST Q34

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of thermometer names after major party Presidential candidate thermometers

Question

(How would you rate:) J.D. Vance

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_THPORVPC, PAPI POST Q33

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of thermometer names after major party Presidential candidate thermometers

Question

(How would you rate:) Joe Biden

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMPO_BIDEN, PAPI POST Q30

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Order of thermometer names after major party Presidential candidate thermometers

Question

(How would you rate:) Christian Fundamentalists

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRFUND, PAPI POST Q54

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Feminists

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRFEM, PAPI POST Q51

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Liberals

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRLIB, PAPI POST Q35

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Labor unions

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRLAB, PAPI POST Q57

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Big business

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRBIGB, PAPI POST Q58

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Conservatives

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRCONS, PAPI POST Q36

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) The U.S. Supreme Court

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRSCT, PAPI POST Q37

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Gay men and lesbians

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRGAY, PAPI POST Q49

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Congress

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRCONG, PAPI POST Q38

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Muslims

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRMUSL, PAPI POST Q48

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Christians

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRXTIAN

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Variable Note

This question was only asked in the FTF/WEB instrument.

Question

(How would you rate:) MAGA movement

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_THGRMAGA, PAPI POST Q55

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Jews

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_JEWS, PAPI POST Q47

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Police

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_POLICE, PAPI POST Q40

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Transgender people

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_TRANS, PAPI POST Q50

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) Black Lives Matter movement

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_BLM, PAPI POST Q56

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 1: Randomize the order of THGRFUND, THGRFEM, THGRLIB, THGRLAB, THGRBIGB, THGRCONS, THGRSCT, THGRGAY, THGRCONG, THGRMUSL, THGRXTIAN, THGRMAGA, JEWS, POLICE, TRANS, BLM

Question

(How would you rate:) The National Rifle Association (NRA)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_NRA, PAPI POST Q41

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 2: Randomize the order of NRA, FBI, RURAL, PLANPARENT

Question

(How would you rate:) The Federal Bureau of Investigation (FBI)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_FBI, PAPI POST Q39

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 2: Randomize the order of NRA, FBI, RURAL, PLANPARENT

Question

(How would you rate:) Rural Americans

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_RURAL, PAPI POST Q52

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 2: Randomize the order of NRA, FBI, RURAL, PLANPARENT

Question

(How would you rate:) Planned Parenthood

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
998. Don’t know (where to rate)
999. Don’t recognize

Survey Question(s)

THERMGR_PLANPARENT, PAPI POST Q42

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Set 2: Randomize the order of NRA, FBI, RURAL, PLANPARENT

Question

In general, do you approve or disapprove of the way your U.S. House representative has been handling their job?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

INCUMBHS_HINCAPP

Question

Do you approve strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

INCUMBHS_HINCAPPSTR

Universe

IF R APPROVES HOUSE INCUMBENT JOB:

Question

Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

INCUMBHS_HINDISSTR

Universe

IF R DISAPPROVES HOUSE INCUMBENT JOB:

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242160, V242161 or V242162
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

INCUMBHS_HINCAPP, INCUMBHS_HINCAPPSTR, INCUMBHS_HINDISSTR

Question

How good a job would you say your U.S. House representative does of keeping in touch with the people in your district – do they do [a very good job, fairly good, fairly poor, or a very poor job / a very poor job, fairly poor, fairly good, or very good job] of keeping in touch with the people in this district?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very good
2. Fairly good
3. Fairly poor
4. Very poor

Survey Question(s)

INCUMBHS_HINCTOUCH

Response Order

Forward/Reverse order

Question

Switching to another topic. What do you think are the most important problems facing this country? If you think there are more than one, please briefly tell me one problem now.

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

MIP_PROB1, PAPI POST Q59

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Switching to another topic. What do you think are the most important problems facing this country? If you think there are more than one, please briefly tell me one problem now.

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient parital, interview deleted
-6. No post interview
-4. Respondent - other (self reference without problem mention)
-1. Inapplicable

See APPENDIX B: “MOST IMPORTANT PROBLEM” CODES for codes 1-990.

Survey Question(s)

MIP_PROB1, PAPI POST Q59

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Switching to another topic. What do you think are the most important problems facing this country? If you think there are more than one, please briefly tell me one problem now.

Value Labels

Survey Question(s)

MIP_PROB1, PAPI POST Q59

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Switching to another topic. What do you think are the most important problems facing this country? If you think there are more than one, please briefly tell me one problem now.

Value Labels

Survey Question(s)

MIP_PROB1, PAPI POST Q59

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Switching to another topic. What do you think are the most important problems facing this country? If you think there are more than one, please briefly tell me one problem now.

Value Labels

Survey Question(s)

MIP_PROB1, PAPI POST Q59

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Switching to another topic. What do you think are the most important problems facing this country? If you think there are more than one, please briefly tell me one problem now.

Value Labels

Survey Question(s)

MIP_PROB1, PAPI POST Q59

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Which political party do you think would be the most likely to get the government to do a better job in dealing with this problem – [the Democrats, the Republicans / the Republicans, the Democrats] or wouldn’t there be much difference between them?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democrats
2. Republicans
3. Wouldn’t be much difference

Survey Question(s)

MIP_PROB1PTY, PAPI POST Q60

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF FIRST MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK OR REFUSED:

Randomization

Order of party names in question text (same order used for all mentions if R mentions more than 1 problem).
Order of response options 1-2 (randomized same, do not use candidateorder)

Response Order

Randomize 2 major parties

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

MIP_PROB2

Universe

IF FIRST MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB2

Universe

IF FIRST MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB2

Universe

IF FIRST MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB2

Universe

IF FIRST MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB2

Universe

IF FIRST MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB2

Universe

IF FIRST MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Value Labels

Survey Question(s)

MIP_PROB2PTY

Universe

IF SECOND MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Randomization

Order of party names in question text (same order used for all mentions
if R mentions more than 1 problem).
Order of response options 1-2 (randomized same, do not use candidateorder)

Response Order

Randomize 2 major parties

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

MIP_PROB3

Universe

IF SECOND MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB3

Universe

IF SECOND MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB3

Universe

IF SECOND MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB3

Universe

IF SECOND MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB3

Universe

IF SECOND MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Can you think of any other important problems facing this country? If so, please briefly mention one of them now.

Value Labels

Survey Question(s)

MIP_PROB3

Universe

IF SECOND MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Value Labels

Survey Question(s)

MIP_PROB3PTY

Universe

IF THIRD MENTION OF MOST IMPORTANT PROBLEM IS NOT DK, SK, OR REFUSED:

Randomization

Order of party names in question text (same order used for all mentions
if R mentions more than 1 problem).
Order of response options 1-2 (randomized same, do not use candidateorder)

Response Order

Randomize 2 major parties

Question

Of those you’ve mentioned, what would you say is the single most important problem the country faces?

Value Labels

-2. Open-end responses available in separate file

Survey Question(s)

MIP_MOSTPROB

Universe

IF R HAS MENTIONED MORE THAN 1 IMPORTANT PROBLEM IN THE COUNTRY:

Question

Of those you’ve mentioned, what would you say is the single most important problem the country faces?

Value Labels

Survey Question(s)

MIP_MOSTPROB

Universe

IF R HAS MENTIONED MORE THAN 1 IMPORTANT PROBLEM IN THE COUNTRY:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Of those you’ve mentioned, what would you say is the single most important problem the country faces?

Value Labels

Survey Question(s)

MIP_MOSTPROB

Universe

IF R HAS MENTIONED MORE THAN 1 IMPORTANT PROBLEM IN THE COUNTRY:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Of those you’ve mentioned, what would you say is the single most important problem the country faces?

Value Labels

Survey Question(s)

MIP_MOSTPROB

Universe

IF R HAS MENTIONED MORE THAN 1 IMPORTANT PROBLEM IN THE COUNTRY:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Of those you’ve mentioned, what would you say is the single most important problem the country faces?

Value Labels

Survey Question(s)

MIP_MOSTPROB

Universe

IF R HAS MENTIONED MORE THAN 1 IMPORTANT PROBLEM IN THE COUNTRY:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

Of those you’ve mentioned, what would you say is the single most important problem the country faces?

Value Labels

Survey Question(s)

MIP_MOSTPROB

Universe

IF R HAS MENTIONED MORE THAN 1 IMPORTANT PROBLEM IN THE COUNTRY:

Variable Note

Coded data for this variable that was previously unreleased were added to the full release version (20260519) of the 2024 Time Series data.

Question

How important is the following issue in the country today? [Extremely important, very important, moderately important, slightly important or not at all important / Not at all important, slightly important, moderately important, very important or extremely important]?

Illegal immigration

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. Slightly important
5. Not at all important

Survey Question(s)

IMP_ILLIMMIG, PAPI POST Q109_1

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. Slightly important
5. Not at all important

Survey Question(s)

IMP_COST, PAPI POST Q109_2

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. Slightly important
5. Not at all important

Survey Question(s)

IMP_CLIMCHNG, PAPI POST Q109_3

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

Survey Question(s)

IMP_GUN, PAPI POST Q109_4

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

How important is following issue in the country today? [Extremely important, very important, moderately important, slightly important or not at all important / Not at all important, slightly important, moderately important, very important or extremely important]?

Abortion

Value Labels

Survey Question(s)

IMP_ABRT, PAPI POST Q109_5

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Extremely important
2. Very important
3. Moderately important
4. Slightly important
5. Not at all important

Survey Question(s)

IMP_CRIME, PAPI POST Q109_6

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

Survey Question(s)

IMP_GAZAWAR, PAPI POST Q109_7

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

Survey Question(s)

IMP_PUBSCHL, PAPI POST Q109_8

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

Survey Question(s)

IMP_DEMOC, PAPI POST Q109_9

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Value Labels

Survey Question(s)

IMP_RACEINEQ, PAPI POST Q109_10

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

RANDOMIZE ITEMS: ILLIMMIG, COST, CLIMCHNG, GUN, ABRT, CRIME, GAZAWAR, PUBSCHL, DEMOC, RACEINEQ

Response Order

Forward/Reverse order

Question

Please tell us which political party — the [Democrats/Republicans] or the [Republicans/Democrats] — would do a better job handling the following issue, or is there no difference.

Illegal immigration

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

OWN_OWNILLIMIG, PAPI POST Q110_1

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize the order of OWNILLIMIG, OWNCOST, OWNCLIMCHNG, OWNABRT, OWNCRIME, OWNPUBSCHL

Response Order

Randomize 2 major parties

Question

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

OWN_OWNCOST, PAPI POST Q110_2

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize the order of OWNILLIMIG, OWNCOST, OWNCLIMCHNG, OWNABRT, OWNCRIME, OWNPUBSCHL

Response Order

Randomize 2 major parties

Question

Please tell us which political party — the [Democrats/Republicans] or the [Republicans/Democrats] — would do a better job handling the following issue, or is there no difference.

Climate change

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

OWN_OWNCLIMCHNG, PAPI POST Q110_3

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize the order of OWNILLIMIG, OWNCOST, OWNCLIMCHNG, OWNABRT, OWNCRIME, OWNPUBSCHL

Response Order

Randomize 2 major parties

Question

Please tell us which political party—the Democrats or the Republicans—would do a better job handling each of the following issues, or is there no difference? Gun policy

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

PAPI POST Q110_4

Variable Note

This question was only asked in the PAPI instrument.

Question

Please tell us which political party — the [Democrats/Republicans] or the [Republicans/Democrats] — would do a better job handling the following issue, or is there no difference.

Abortion

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

OWN_OWNABRT,PAPI POST Q110_5

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize the order of OWNILLIMIG, OWNCOST, OWNCLIMCHNG, OWNABRT, OWNCRIME, OWNPUBSCHL

Response Order

Randomize 2 major parties

Question

Please tell us which political party — the [Democrats/Republicans] or the [Republicans/Democrats] — would do a better job handling the following issue, or is there no difference.

Crime

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

OWN_OWNCRIME, PAPI POST Q110_6

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize the order of OWNILLIMIG, OWNCOST, OWNCLIMCHNG, OWNABRT, OWNCRIME, OWNPUBSCHL

Response Order

Randomize 2 major parties

Question

Please tell us which political party—the Democrats or the Republicans—would do a better job handling each of the following issues, or is there no difference? The war in Gaza

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

PAPI POST Q110_7

Variable Note

This question was only asked in the PAPI instrument.

Question

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

OWN_OWNPUBSCHL, PAPI POST Q110_8

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize the order of OWNILLIMIG, OWNCOST, OWNCLIMCHNG, OWNABRT, OWNCRIME, OWNPUBSCHL

Response Order

Randomize 2 major parties

Question

Please tell us which political party—the Democrats or the Republicans—would do a better job handling each of the following issues, or is there no difference? Keeping the U.S. a democracy

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

PAPI POST Q110_9

Variable Note

This question was only asked in the PAPI instrument.

Question

Please tell us which political party—the Democrats or the Republicans—would do a better job handling each of the following issues, or is there no difference? Racial inequality

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Democrats
2. Republicans
3. No difference

Survey Question(s)

PAPI POST Q110_10

Variable Note

This question was only asked in the PAPI instrument.

Question

For the following statements, please tell me how strongly you agree or disagree:

‘Public officials don’t care much what people like me think.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Agree strongly
2. Agree somewhat
3. Neither agree nor disagree
4. Disagree somewhat
5. Disagree strongly

Survey Question(s)

EFFICPO_CARESTD, PAPI POST Q61

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

‘People like me don’t have any say about what the government does.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

Survey Question(s)

EFFICPO_SAYSTD, PAPI POST Q62

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How often do politics and government seem so complicated that you can’t really understand what’s going on? [Always, most of the time, about half the time, some of the time, or never / Never, some of the time, about half the time, most of the time, or always] ?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Always
2. Most of the time
3. About half the time
4. Some of the time
5. Never

Survey Question(s)

EFFICPO_COMPLICREV, PAPI POST Q64

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How well do you understand the important political issues facing our country? [Extremely well, very well, moderately well, slightly well, or not well at all / Not well at all, slightly well, moderately well, very well, or extremely well]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely well
2. Very well
3. Moderately well
4. Slightly well
5. Not well at all

Survey Question(s)

EFFICPO_UNDREV

Response Order

Forward/Reverse order

Question

Next, do you think there are any important differences in what the Republicans and Democrats stand for?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes, differences
2. No, no differences

Survey Question(s)

PTYDIFF_IMPDIFFPTY, PAPI POST Q63

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Would you say that one of the parties is more conservative than the other at the national level?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes, one party more conservative
2. No, one party not more conservative

Survey Question(s)

PTYCONS_PTYCONS

Question

Which party is more conservative?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democrats
2. Republicans

Survey Question(s)

PTYCONS_PTYCONSWH

Universe

IF R SAYS THAT ONE OF THE MAJOR PARTIES IS MORE CONSERVATIVE:

Question

In your view, how often do the following things occur in this country’s elections:

Votes are counted fairly? [All of the time, most of the time, about half of the time, some of the time, or never / Never, some of the time, about half of the time, most of the time, or all of the time]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. All of the time
2. Most of the time
3. About half of the time
4. Some of the time
5. Never

Survey Question(s)

ELECTINTPO_COUNTFAIR, PAPI POST Q65

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How important is it that more Hispanics be elected to political office? [Extremely important, very important, moderately important, a little important, or not at all important / Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

Survey Question(s)

ELECTMORE_HISP

Response Order

Forward/Reverse order

Question

How important is it that more blacks be elected to political office? [Extremely important, very important, moderately important, a little important, or not at all important / Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

Survey Question(s)

ELECTMORE_BLACK

Response Order

Forward/Reverse order

Question

How important is it that more Asians be elected to political office? [Extremely important, very important, moderately important, a little important, or not at all important / Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

Survey Question(s)

ELECTMORE_ASIAN

Response Order

Forward/Reverse order

Question

How important is it that more lesbian, gay, bisexual, and transgender people be elected to political office? [Extremely important, very important, moderately important, a little important, or not at all important / Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

Survey Question(s)

ELECTMORE_LGBT

Response Order

Forward/Reverse order

Question

How important is it that more women be elected to political office? [Extremely important, very important, moderately important, a little important, or not at all important / Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

Survey Question(s)

ELECTMORE_WOMEN

Response Order

Forward/Reverse order

Question

How important is it to you for a woman to be elected President of the United States? [ Extremely important, very important, moderately important, a little important, or not at all important /Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

Survey Question(s)

WOMANPRES_ELECT

Response Order

Forward/Reverse order

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

Do you favor, oppose, or neither favor nor oppose placing limits on political campaign spending?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

CAMPFIN_SPENDLIM

Randomization

Order of CAMPFIN questions in module, 8 possible orderings:
1) donate,spendlim,org,direct
2) donate,spendlim,direct,org
3) donate,org,direct,spendlim
4) donate,direct,org,spendlim
5) spendlim,org,direct,donate
6) spendlim,direct,org,donate
7) org,direct,spendlim,donate
8) direct,org,spendlim,donate

Question

When organizations spend ^indirect_amt on advertising to support candidates for Congress, how much does Congress respond by passing laws to benefit those organizations? [A great deal, a lot, a moderate amount, a little, or not at all / Not at all, a little, a moderate amount, a lot, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A lot
3. A moderate amount
4. A little
5. Not at all

Survey Question(s)

CAMPFIN_ORG

Randomization

Response Order

Forward/Reverse order

Variable Note

The variable ^indirect_amt is assigned one of two values - $2,500 or $250,000 - based on a randomly generated value.

Question

When people give ^direct_amt each to the election campaigns of Members of Congress, how much does Congress respond by passing laws to benefit people who gave them money? [A great deal, a lot, a moderate amount, a little, or not at all / Not at all, a little, a moderate amount, a lot, or a great deal]?

Value Labels

Survey Question(s)

CAMPFIN_DIRECT

Randomization

Response Order

Forward/Reverse order

Variable Note

The variable ^direct_amt is assigned one of five values - $25, $250, $1,000, $2,500, or $5,000 - based on a randomly generated value.

Question

How often do Members of Congress change their votes on legislation because someone donates money to their campaign? [All the time, very often, a moderate amount of time, rarely, or never / Never, rarely, a moderate amount of time, very often, or all the time]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. All the time
2. Very often
3. A moderate amount of time
4. Rarely
5. Never

Survey Question(s)

CAMPFIN_DONATE

Randomization

Response Order

Forward/Reverse order

Question

Have the courts treated Donald Trump fairly or unfairly?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Fairly
2. Unfairly

Survey Question(s)

TRUMPPOST_COURTFAIRPO, PAPI POST Q67

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

How strongly do you feel that way? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

TRUMPPOST_COURTFAIRSTRPO, PAPI POST Q68

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF R THINKS COURTS TREATED DONALD TRUMP FAIRLY:
IF R THINKS COURTS TREATED DONALD TRUMP UNFAIRLY /

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242218 or V242219
-1. Inapplicable
1. Feels very strongly courts treated Trump fairly
2. Feels somewhat strongly courts treated Trump fairly
3. Feels not strongly courts treated Trump fairly
4. Feels not strongly courts treated Trump unfairly
5. Feels somwhat strongly courts treated Trump unfairly
6. Feels very strongly courts treated Trump unfairly

Survey Question(s)

TRUMPPOST_COURTFAIRPO, TRUMPPOST_COURTFAIRSTRPO, PAPI POST Q67, PAPI POST Q68

Question

Do you approve or disapprove of Joe Biden dropping out of the presidential race?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Approve
2. Disapprove

Survey Question(s)

CANDPOST_BIDENDROPPO

Question

Do you approve strongly or not strongly / Do you disapprove strongly or not strongly?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

CANDPOST_BIDENDROPSTRPO

Universe

IF R APPROVES BIDEN DROPPING OUT OF PRESIDENTIAL RACE /
IF R DISAPPROVES BIDEN DROPPING OUT OF PRESIDENTIAL RACE:

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242221 or V242222
-1. Inapplicable
1. Approve strongly
2. Approve not strongly
3. Disapprove not strongly
4. Disapprove strongly

Survey Question(s)

CANDPOST_BIDENDROPPO, CANDPOST_BIDENDROPSTRPO

Question

Some people have suggested placing new limits on foreign imports in order to protect American jobs. Others say that such limits would raise consumer prices and hurt American exports. Do you favor or oppose placing new limits on imports?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose

Survey Question(s)

IMPORTS_IMPORTLIM

Question

Do you [favor / oppose] placing new limits on imports strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

IMPORTS_IMPORTLIMSTR

Universe

IF R FAVORS PLACING NEW LIMITS ON IMPORTS /
IF R OPPOSES PLACING NEW LIMITS ON IMPORTS:

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242224 or V242225
-1. Inapplicable
1. Favor strongly
2. Favor not strongly
3. Oppose not strongly
4. Oppose strongly

Survey Question(s)

IMPORTS_IMPORTLIM, IMPORTS_IMPORTLIMSTR

Question

Do you think the number of immigrants from foreign countries who are permitted to come to the United States to live should be [increased a lot, increased a little, left the same as it is now, decreased a little, or decreased a lot / decreased a lot, decreased a little, left the same as it is now, increased a little, or increased a lot]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Increased a lot
2. Increased a little
3. Left the same as it is now
4. Decreased a little
5. Decreased a lot

Survey Question(s)

IMMIGPO_IMMLEVEL, PAPI POST Q69

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Now I’d like to ask you about immigration in recent years.

How likely is it that recent immigration levels will take jobs away from people already here – [extremely likely, very likely, somewhat likely, or not at all likely / not at all likely, somewhat likely, very likely, or extremely likely]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely likely
2. Very likely
3. Somewhat likely
4. Not at all likely

Survey Question(s)

IMMIGPO_IMMJOBS

Response Order

Forward/Reverse order

Question

Does illegal immigration increase, decrease, or have no effect on the crime rate in the U.S.?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Increase
2. Decrease
3. Have no effect

Survey Question(s)

IMMIGPO_ILLIMCRIME

Question

Does it [increase / decrease] the crime rate [a lot, a moderate amount, or a little / a little, a moderate amount, or a lot]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A lot
2. A moderate amount
3. A little

Survey Question(s)

IMMIGPO_ILLIMCRIMESTR

Universe

IF R SAYS INCREASES CRIME RATE /
IF R SAYS DECREASES CRIME RATE:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242229 or V242230
-1. Inapplicable
1. Increate a lot
2. Increase a moderate amount
3. Increase a little
4. Have no effect
5. Decrease a little
6. Decrease a moderate amount
7. Decrease a lot

Survey Question(s)

IMMIGPO_ILLIMCRIME, IMMIGPO_ILLIMCRIMESTR

Question

Do you favor, oppose, or neither favor nor oppose providing a path to citizenship for unauthorized immigrants who obey the law, pay a fine, and pass security checks?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

IMMIGPO_PATHWAY

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-8. Don’t Know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

IMMIGPO_PATHWAYSTR

Universe

IF R FAVORS PROVIDING A PATH TO CITIZENSHIP /
IF R OPPOSES PROVIDING A PATH TO CITIZENSHIP:

Response Order

Forward/Reverse order

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242232 or V242233
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

IMMIGPO_PATHWAY, IMMIGPO_PATHWAYSTR

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

Are immigrants generally good or bad for America’s economy?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely good
2. Moderately good
3. Slightly good
4. Neither good nor bad
5. Slightly bad
6. Moderately bad
7. Extremely bad

Survey Question(s)

IMMIGPO_ECONIMM

Question

How important is it for immigrants to adapt to the customs and traditions of the United States?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all important
2. A little important
3. Moderately important
4. Very important
5. Extremely important

Survey Question(s)

IMMIGPO_CUSTOMS

Response Order

Forward/Reverse order

Question

What about your opinion – are you for or against preferential hiring and promotion of blacks?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. For preferential hiring and promotion of blacks
2. Against preferential hiring and promotion of blacks

Survey Question(s)

AFFIRM_AFFOPIN

Question

Do you favor preference in hiring and promotion strongly or not strongly?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

AFFIRM_AFFFAV

Universe

IF R IS FOR PREFERENTIAL HIRING AND PROMOTION FOR BLACKS:

Question

Do you oppose preference in hiring and promotion strongly or not strongly?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Strongly
2. Not strongly

Survey Question(s)

AFFIRM_AFFOPP

Universe

IF R IS AGAINST PREFERENTIAL HIRING AND PROMOTION FOR BLACKS:

Question

Some people say that because of past discrimination, blacks should be given preference in hiring and promotion. Others say that such preference in hiring and promotion of blacks is wrong because it gives blacks advantages they haven’t earned. What about your opinion—are you for or against preferential hiring and promotion of blacks, and how strongly?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Strongly for preferential hiring and promotion of blacks
2. Not strongly for preferential hiring and promotion of blacks
3. Not strongly against preferential hiring and promotion of blacks
4. Strongly against preferential hiring and promotion of blacks

Survey Question(s)

PAPI POST Q70

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-2. DK/RF in V242237, V242238, V242239, V242240
1. Strongly for preferential hiring and promotion of blacks
2. Not strongly for preferential hiring and promotion of blacks
3. Not strongly against preferential hiring and promotion of blacks
4. Strongly against preferential hiring and promotion of blacks

Survey Question(s)

AFFIRM_AFFOPIN, AFFIRM_AFFFAV, AFFIRM_AFFOPP, PAPI POST Q70

Question

Do you favor, oppose, or neither favor nor oppose allowing universities to increase the number of black students studying at their schools by considering race along with other factors when choosing students?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

AFFPRE_AAUNI

Question

Do you favor that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

AFFPRE_AAUNIFAV

Universe

IF R FAVORS AFFIRMATIVE ACTION AT UNIVERSITIES:

Response Order

Forward/Reverse order

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

Do you oppose that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

AFFPRE_AAUNIOPP

Universe

IF R OPPOSES AFFIRMATIVE ACTION AT UNIVERSITIES:

Response Order

Forward/Reverse order

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242242 or V242243
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

AFFPRE_AAUNI, AFFPRE_AAUNIFAV, AFFPRE_AAUNIOPP

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

Which of the following statements comes closer to your view?

One, the less government, the better; or Two, there are more things that government should be doing.

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. The less government the better
2. More things government should be doing

Survey Question(s)

LIMTGOV_LESSGOVT

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

How strongly do you feel this way? [Very strongly, somewhat strongly, or not strongly / Not strongly, somewhat strongly, or very strongly]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very strongly
2. Somewhat strongly
3. Not strongly

Survey Question(s)

LIMTGOV_LESSGOVTSTR

Universe

IF R BELIEVES LESS GOVERNMENT IS BETTER /
IF R BELIEVES THERE ARE MORE THINGS FOR THE GOVERNMENT TO DO:

Response Order

Forward/Reverse order

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242246 or V242247
-1. Inapplicable
1. Feels very strongly the less gov the better
2. Feels somewhat strongly the less gov the better
3. Feels not strongly the less gov the better
4. Feels not strongly there is more gov should be doing
5. Feels somewhat strongly there is more gov should be doing
6. Feels very strongly there is more gov should be doing

Survey Question(s)

LIMTGOV_LESSGOVT, LIMTGOV_LESSGOVTSTR

Variable Note

Significant data corrections were made to this variable for the full release version (20260519) of the 2024 Time Series data.

Question

Would it be good for society to have [more government regulation, about the same amount of regulation as there is now, or less government regulation / less government regulation, about the same amount of regulation as there is now, or more government regulation]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much more
2. Somewhat more
3. A little more
4. About the same amount
5. A little less
6. Somewhat less
7. Much less

Survey Question(s)

LIMTGOV_REGULATE

Response Order

Forward/Reverse order

Question

Next, do you favor, oppose, or neither favor nor oppose the government trying to reduce the difference in incomes between the richest and poorest households?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

LIMTGOV_INEQRED

Question

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

LIMTGOV_INEQREDSTR

Universe

IF R FAVORS GOVT REDUCING DIFFERENCES /
IF R OPPOSES GOVT REDUCING DIFFERENCE:

Response Order

Forward/Reverse order

Question

Do you favor or oppose, or neither favor nor oppose the government trying to reduce the difference in incomes between the richest and poorest households?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

PAPI POST Q71

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2 DK/RF in V242250 or V242251
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

LIMTGOV_INEQRED, LIMTGOV_INEQREDSTR, PAPI POST Q71

Variable Note

Significant data corrections were made to this variable for the full release version (20250808) of the 2024 Time Series data.

Question

‘Our society should do whatever is necessary to make sure that everyone has an equal opportunity to succeed.’

Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Agree strongly
2. Agree somewhat
3. Neither agree nor disagree
4. Disagree somewhat
5. Disagree strongly

Survey Question(s)

EGAL_DONECESS, PAPI POST Q72

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

‘This country would be better off if we worried less about how equal people are.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Agree strongly
2. Agree somewhat
3. Neither agree nor disagree
4. Disagree somewhat
5. Disagree strongly

Survey Question(s)

EGAL_WORRYLESS, PAPI POST Q73

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

‘It is not really that big a problem if some people have more of a chance in life than others.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

Survey Question(s)

EGAL_NOTBIGPROB, PAPI POST Q74

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

‘If people were treated more equally in this country we would have many fewer problems.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

Survey Question(s)

EGAL_FEWERPROBS, PAPI POST Q75

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

‘The world is always changing and we should adjust our view of moral behavior to those changes.’

Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?

Value Labels

Survey Question(s)

MORALTRAD_ADJMORAL

Response Order

Forward/Reverse order

Question

‘This country would have many fewer problems if there were more emphasis on traditional family ties.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

Survey Question(s)

MORALTRAD_MORETRAD

Response Order

Forward/Reverse order

Question

Please tell me which one you think is more important for a child to have: Independence or respect for elders

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Independence
2. Respect for elders
3. Both {VOL}
4. Neither {VOL}

Survey Question(s)

AUTH_CHILDIND

Question

(Which one is more important for a child to have:) Curiosity or good manners

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Curiosity
2. Good manners
3. Both {VOL}
4. Neither {VOL}

Survey Question(s)

AUTH_CHILDCUR

Question

(Which one is more important for a child to have:) Obedience or self-reliance

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Obedience
2. Self-reliance
3. Both {VOL}
4. Neither {VOL}

Survey Question(s)

AUTH_CHILDOBED

Question

(Which one is more important for a child to have:) Being considerate or well behaved

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Being considerate
2. Well behaved
3. Both {VOL}
4. Neither {VOL}

Survey Question(s)

AUTH_CHILDCONSID

Question

Generally speaking, is the United States better, worse, or about the same as most other countries?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Better
2. Worse
3. The same

Survey Question(s)

NATLSM_USOTHCNTRY

Question

Is that [a lot better or somewhat better / somewhat better or a lot better]? / Is that [a lot worse or somewhat worse / somewhat worse or a lot worse]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A lot
2. Somewhat

Survey Question(s)

NATLSM_USOTHCNTRYSTR

Universe

IF R THINKS US IS BETTER /
IF R THINKS US IS WORSE:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242264 or V242265
-1. Inapplicable
1. A lot better
2. Somewhat better
3. The same
4. Somewhat worse
5. A lot worse

Survey Question(s)

NATLSM_USOTHCNTRY, NATLSM_USOTHCNTRYSTR

Question

Compared to people living in cities, do people living in small towns and rural areas get more, the same, or less than they deserve from the government?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. More
2. The same
3. Less

Survey Question(s)

RURALRES_DESGOVT

Question

[Do they get [a great deal more, moderately more, or a little more / a little more, moderately more, or a great deal more] than they deserve from the government? / Do they get [a great deal less, moderately less, or a little less / a little less, moderately less, or a great deal less] than they deserve from the government?]

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. Moderately
3. A little

Survey Question(s)

RURALRES_DESGOVTSTR

Universe

IF R THINKS RURAL AREAS GET MORE THAN THEY DESERVE /
IF R THINKS RURAL AREAS GET LESS THAN THEY DESERVE:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242267 or V242268
-1. Inapplicable
1. A great deal more
2. Moderately more
3. A little more
4. The same
5. A little less
6. Moderately less
7. A great deal less

Survey Question(s)

RURALRES_DESGOVT, RURALRES_DESGOVTSTR

Question

Compared to people living in cities, do people living in small towns and rural areas have too much influence, too little influence, or about the right amount of influence on government?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

RURALRES_INFGOVT

Question

[Do they have [much too much, somewhat too much, or a bit too much / a bit too much, somewhat too much, or much too much] influence on government? / Do they have [much too little, somewhat too little, or a bit too little / a bit too little, somewhat too little, or much too little] influence on government?]

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much too much / Much too little
2. Somewhat too much / Somewhat too little
3. A bit too much / A bit too little

Survey Question(s)

RURALRES_INFGOVTSTR

Universe

IF R THINKS RURAL AREAS HAVE TOO MUCH INFLUENCE /
IF R THINKS RURAL AREAS HAVE TOO LITTLE INFLUENCE:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF IN V242270 or V242271
-1. Inapplicable
1. Much too much
2. Somewhat too much
3. A bit too much
4. About the right amount
5. A bit too little
6. Somewhat too little
7. Much too little

Survey Question(s)

RURALRES_INFGOVT, RURALRES_INFGOVTSTR

Question

Do people living in small towns and rural areas get too much respect, too little respect, or about the right amount of respect from people living in cities?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

RURALRES_RESPECT

Question

[Do they get [much too much, somewhat too much, or a bit too much / a bit too much, somewhat too much, or much too much] respect from people living in cities? / Do they get [much too little, somewhat too little, or a bit too little / a bit too little, somewhat too little, or much too little] respect from people living in cities?]

Value Labels

Survey Question(s)

RURALRES_RESPECTSTR

Universe

IF R THINKS RURAL AREAS GET TOO MUCH RESPECT /
IF R THINKS RURAL AREAS GET TOO LITTLE RESPECT:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF IN V242273 or V242274
-1. Inapplicable
1. Much too much
2. Somewhat too much
3. A bit too much
4. About the right amount
5. A bit too little
6. Somewhat too little
7. Much too little

Survey Question(s)

RURALRES_RESPECT, RURALRES_RESPECTSTR

Question

Do you think it is better, worse, or makes no difference for the family as a whole if the man works outside the home and the woman takes care of the home and family?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Better
2. Worse
3. Makes no difference

Survey Question(s)

GENROLES_WKWIFE, PAPI POST Q79

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Is it [much better, somewhat better, or slightly better / slightly better, somewhat better, or much better]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much
2. Somewhat
3. Slightly

Survey Question(s)

GENROLES_WKWBETT

Universe

IF R SAYS IT IS BETTER FOR THE MAN TO WORK AND THE WOMAN TO STAY AT HOME:

Response Order

Forward/Reverse order

Question

Is it [much worse, somewhat worse, or slightly worse / slightly worse, somewhat worse, or much worse]?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much
2. Somewhat
3. Slightly

Survey Question(s)

GENROLES_WKWWRS

Universe

IF R SAYS IT IS WORSE FOR THE MAN TO WORK AND THE WOMAN TO STAY AT HOME:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2 DK/RF in V242276, V242277, V242278
-1. Inapplicable
1. Much better
2. Somewhat better
3. Slightly better
4. Makes no difference
5. Slightly worse
6. Somewhat worse
7. Much worse

Survey Question(s)

GENROLES_WKWIFE, GENROLES_WKWBETT, GENROLES_WKWWRS

Question

When women demand equality these days, how often are they actually seeking special favors? [always, most of the time, about half the time, some of the time, or never / never, some of the time, about half the time, most of the time, or always]?

Value Labels

Survey Question(s)

MODSEXM_SPECFAV

Response Order

Forward/Reverse order

Question

When women complain about discrimination, how often do they cause more problems than they solve? [always, most of the time, about half the time, some of the time, or never / never, some of the time, about half the time, most of the time, or always]?

Value Labels

Survey Question(s)

MODSEXM_COMDISC

Response Order

Forward/Reverse order

Question

‘Irish, Italian, Jewish and many other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors.’

Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?

Value Labels

Survey Question(s)

RESENT_WORKWAY

Response Order

Forward/Reverse order

Question

‘Generations of slavery and discrimination have created conditions that make it difficult for blacks to work their way out of the lower class.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

Survey Question(s)

RESENT_GENRTNS, PAPI POST Q76

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

‘Over the past few years, blacks have gotten less than they deserve.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

Survey Question(s)

RESENT_DESERVE, PAPI POST Q77

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

‘It’s really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites.’

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly / disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with this statement?)

Value Labels

Survey Question(s)

RESENT_TRYHARD, PAPI POST Q78

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How well does the following statement describe your view?

“Our political system only works for the insiders with money and power.”

[Not at all well, not very well, somewhat well, very well, or extremely well / Extremely well, very well, somewhat well, not very well, or not at all well]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all well
2. Not very well
3. Somewhat well
4. Very well
5. Extremely well

Survey Question(s)

ANTIELITE_ELITEINSIDER, PAPI POST Q80

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How well does the following statement describe your view?

“Because of the rich and powerful, it becomes difficult for the rest of us to get ahead.”

[Not at all well, not very well, somewhat well, very well, or extremely well / Extremely well, very well, somewhat well, not very well, not at all well]?

Value Labels

Survey Question(s)

ANTIELITE_ELITEAHEAD, PAPI POST Q81

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Do you think you get more than your fair share in life, less than your fair share, or about the right amount?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. More
2. Less
3. About right

Survey Question(s)

VICTIM_FAIRSHARE

Question

How much [more/less]? [A great deal, a moderate amount, or a little / A little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

VICTIM_FAIRSHARESTR

Universe

IF R THINKS THEY GET MORE THAN THEIR FAIR SHARE/
IF R THINKS THEY GET LESS THAN THEIR FAIR SHARE:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242306 or V242307
-1. Inapplicable
1. A great deal more
2. A moderate amount more
3. A little more
4. About right
5. A little less
6. A moderate amount less
7. A great deal less

Survey Question(s)

VICTIM_FAIRSHARE, VICTIM_FAIRSHARESTR

Question

On a scale from not at all masculine to completely masculine, where would you place yourself? Not at all, a little, moderately, mostly, or completely?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Mostly
5. Completely

Survey Question(s)

GENDID_GENDMASC

Randomization

RANDOMIZE ORDER OF GENDMASC & GENDFEM

Question

On a scale from not at all feminine to completely feminine, where would you place yourself? Not at all, a little, moderately, mostly, or completely?

Value Labels

Survey Question(s)

GENDID_GENDFEM

Randomization

RANDOMIZE ORDER OF GENDMASC & GENDFEM

Question

How much opportunity is there in America today for the average person to get ahead? [A great deal, a lot, a moderate amount, a little, or none / None, a little, a moderate amount, a lot, or a great deal]?

Value Labels

Survey Question(s)

ECONMOBIL_INEQOPP, PAPI POST Q82

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

When it comes to people trying to improve their financial well-being, do you think it is now easier, harder, or the same as it was 20 years ago?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Easier
2. Harder
3. The same

Survey Question(s)

ECONMOBIL_INEQRED

Question

How much [easier/harder]? [A great deal, a moderate amount, or a little / A little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

ECONMOBIL_INEQREDAMT

Universe

IF R SAYS ECONOMIC MOBILITY IN U.S. IS EASIER THAN 20 YEARS AGO /
IF R SAYS ECONOMIC MOBILITY IN U.S. IS HARDER THAN 20 YEARS AGO:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242312 or V242313
-1. Inapplicable
1. A great deal easier
2. A moderate amount easier
3. A little easier
4. The same
5. A little harder
6. A moderate amount harder
7. A great deal harder

Survey Question(s)

ECONMOBIL_INEQRED, ECONMOBIL_INEQREDAMT

Question

When the U.S. federal government spends more money than it collects, the difference is called the federal budget deficit. The federal government currently has a deficit.

How important is it to reduce the deficit? [Extremely important, very important, moderately important, a little important, or not at all important / Not at all important, a little important, moderately important, very important, or extremely important]?

Value Labels

Survey Question(s)

BUDGET_DEFIMP

Response Order

Forward/Reverse order

Question

Do you favor, oppose, or neither favor nor oppose increasing income taxes on people making over one million dollars per year?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

TAX_MILLTAX

Question

How much do you favor, oppose, or neither favor nor oppose increasing income taxes on people making over one million dollars per year?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

PAPI POST Q83

Question

Do you favor, oppose, or neither favor nor oppose requiring children to be vaccinated in order to attend public schools?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

VACCINE1_SCHL

Question

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

VACCINE1_SCHLSTR

Universe

IF R FAVORS REQUIRING VACCINATION IN ORDER FOR CHILDREN TO ATTEND SCHOOL /
IF R OPPOSES REQUIRING VACCINATION IN ORDER FOR CHILDREN TO ATTEND SCHOOL:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242317 or V242318
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

VACCINE1_SCHL, VACCINE1_SCHLSTR

Question

How much do you approve, disapprove, or neither approve nor disapprove of the Affordable Care Act of 2010, sometimes called Obamacare?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Approve a great deal
2. Approve a moderate amount
3. Approve a little
4. Neither approve nor disapprove
5. Disapprove a little
6. Disapprove a moderate amount
7. Disapprove a great deal

Survey Question(s)

PAPI POST Q84

Question

How much, if at all, do you think climate change is currently affecting severe weather events or temperature patterns in the United States? [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Not at all
2. A little
3. A moderate amount
4. A lot
5. A great deal

Survey Question(s)

ENVIRPO_WARMUS, PAPI POST Q85

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Do you favor, oppose, or neither favor nor oppose increased government regulation on businesses that produce a great deal of greenhouse emissions linked to climate change?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

ENVIRPO_REGGREEN, PAPI POST Q86

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Variable Note

Significant data corrections were made to this variable for the full release version (20250808) of the 2024 Time Series data.

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

ENVIRPO_REGGREENSTR

Universe

IF R FAVORS INCREASED GOVERNMENT REGULATION /
IF R OPPOSES INCREASED GOVERNMENT REGULATION:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242322 or V242323
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

ENVIRPO_REGGREEN, ENVIRPO_REGGREENSTR

Variable Note

Significant data corrections were made to this variable for the full release version (20250808) of the 2024 Time Series data.

Question

Do you think the federal government should make it more difficult for people to buy a gun than it is now, make it easier for people to buy a gun, or keep these rules about the same as they are now?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. More difficult
2. Easier
3. Keep these rules about the same

Survey Question(s)

GUN_GUNDIFF

Question

Do you favor, oppose, or neither favor nor oppose requiring background checks for gun purchases at gun shows or other private sales?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

GUN_BACKCHECK

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

GUN_BACKCHECKSTR

Universe

IF R FAVORS REQUIRING BACKGROUND CHECKS /
IF R OPPOSES REQUIRING BACKGROUND CHECKS:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242326 or V242327
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

GUN_BACKCHECK, GUN_BACKCHECKSTR

Question

Do you favor, oppose, or neither favor nor oppose banning the sale of semi-automatic “assault-style” rifles?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

GUN_BANAR

Question

Do you [favor / oppose] that [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

GUN_BANARSTR

Universe

IF R FAVORS BANNING ASSAULT-STYLE RIFLES /
IF R OPPOSES BANNING ASSAULT-STYLE RIFLES:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242329 or V242330
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

GUN_BANAR, GUN_BANARSTR

Question

Do you think the federal government should be doing more about the opioid drug addiction issue, should it be doing less, or is it currently doing the right amount?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Should be doing more
2. Should be doing less
3. Is doing the right amount

Survey Question(s)

OPIOID_OPIOID

Question

How much [more / less]? [A great deal, a moderate amount, or a little / A little, a moderate amount, or a great deal]?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

OPIOID_OPIOIDSTR

Universe

IF R SAID GOVT SHOULD DO MORE /
IF R SAID GOVT SHOULD DO LESS:

Response Order

Forward/Reverse order

Question

Do you think the federal government should be doing more about the opioid drug addiction issue, should it be doing less, or is it currently doing the right amount?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Should be doing a great deal more
2. Should be doing a moderate amount more
3. Should be doing a little more
4. Currently doing the right amount
5. Should be doing a little less
6. Should be doing a moderate amount less
7. Should be doing a great deal less

Survey Question(s)

PAPI POST Q87

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-2. DK/RF in V242332, V242333, V242334
1. Should be doing a great deal more
2. Should be doing a moderate amount more
3. Should be doing a little more
4. Currently doing the right amount
5. Should be doing a little less
6. Should be doing a moderate amount less
7. Should be doing a great deal less

Survey Question(s)

OPIOID_OPIOID, OPIOID_OPIOIDSTR, PAPI POST Q87

Question

How often do you think police officers use more force than is necessary? [Never, rarely, about half the time, most of the time, or all the time / All the time, most of the time, about half the time, rarely, or never]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Never
2. Rarely
3. About half the time
4. Most of the time
5. All the time

Survey Question(s)

POLICE_MOREFORCE, PAPI POST Q88

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How would you describe your social class? Are you in the lower class, the working class, the middle class, or the upper class?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Lower class
2. Working class
3. Middle class
4. Upper class

Survey Question(s)

DEMPO_CLASSREV, PAPI POST Q102

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Are you in the lower middle class, the middle class, or the upper middle class?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Lower middle class
2. Middle class
3. Upper middle class

Survey Question(s)

DEMPO_MIDDLECLASS

Universe

IF R HAS INDICATED SOCIAL CLASS AS MIDDLE CLASS:

Question

For information about politics would you say you get the most information from Spanish-language television, radio, and newspapers, or from English-language TV, radio, and newspapers?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. English more
2. Spanish more
3. Both equally (bilingual) {VOL}
5. Other

Survey Question(s)

POHISP_HISPNEWS

Universe

IF R IS IDENTIFIED AS HISPANIC IN PRE-ELECTION IW:

Question

Do you currently live in a rural area, small town, suburb, or city?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Rural area
2. Small town
3. Suburb
4. City

Survey Question(s)

PAPI POST Q21

Question

Regardless of where you currently live, do you usually think of yourself as a city person, a suburban person, a small-town person, a country or rural person, or something else?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. City person
2. Suburban person
3. Small-town person
4. Country (or rural) person
5. Something else {SPECIFY}

Survey Question(s)

URBAN_PLACEID, PAPI POST Q22

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

How important is being a [city person / suburb person / small-town person / country or rural person] to your identity? [Not at all important, a little important, moderately important, very important, or extremely important / Extremely important, very important, moderately important, a little important, or not at all important]?

Value Labels

Survey Question(s)

URBAN_PLACEIDIMP

Universe

IF R IS CITY PERSON /
IF R IS SUBURB PERSON /
IF R IS SMALL-TOWN PERSON /
IF R COUNTRY OR RURAL PERSON

Response Order

Forward/Reverse order

Question

Now for some other questions. How worried are you that the United States will experience a terrorist attack in the near future? [Extremely worried, very worried, moderately worried, slightly worried, or not at all worried / Not at all worried, slightly worried, moderately worried, very worried, or extremely worried]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely worried
2. Very worried
3. Moderately worried
4. Slightly worried
5. Not at all worried

Survey Question(s)

TERROR_TERRWORRY

Response Order

Forward/Reverse order

Question

Do you favor, oppose, or neither favor nor oppose the U.S. making free trade agreements with other countries?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

FREETRADE_AGRMT

Question

How strongly do you [favor / oppose] it? [A great deal, moderately, or a little / A little, moderately, or a great deal]?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. Moderately
3. A little

Survey Question(s)

FREETRADE_AGRMTSTR

Universe

IF R FAVORS U.S FREE TRADE AGREEMENTS WITH OTHER COUNTRIES/
IF R OPPOSES U.S. FREE TRADE AGREEMENTS WITH OTHER COUNTRIES:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242344 or V242345
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

FREETRADE_AGRMT, FREETRADE_AGRMTSTR

Question

Does the increasing number of people of many different races and ethnic groups in the United States make this country a better place to live, a worse place to live, or does it make no difference?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Better
2. Worse
3. Makes no difference

Survey Question(s)

DIVERSITY_INCREASE, PAPI POST Q90

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Does it make it [a lot better or a little better / a little better or a lot better]? / Does it make it [a lot worse or a little worse / a little worse or a lot worse]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A lot
2. A little

Survey Question(s)

DIVERSITY_INCREASESTR

Universe

IF R SAYS DIVERSITY MAKES US BETTER /
IF R SAYS DIVERSITY MAKES US WORSE:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2 DK/RF in V242347 or V242348
-1. Inapplicable
1. A lot better
2. A little better
3. Makes no difference
4. A little worse
5. A lot worse

Survey Question(s)

DIVERSITY_INCREASE, DIVERSITY_INCREASESTR

Question

Should the federal minimum wage be [raised, kept the same, lowered but not eliminated, or eliminated altogether / eliminated altogether, lowered but not eliminated, kept the same, or raised]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Raised
2. Kept the same
3. Lowered
4. Eliminated

Survey Question(s)

ECONEQ_MINWAGE, PAPI POST Q89

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Do you favor an increase, decrease, or no change in government spending to help people pay for health insurance when people can’t pay for it all themselves?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Increase
2. Decrease
3. No change

Survey Question(s)

ECONEQ_GOVHLTHHLP

Question

Should it increase [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]? / Should it decrease [a great deal, a moderate amount, or a little / a little, a moderate amount, or a great deal]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

ECONEQ_GOVHLTHHLPAMT

Universe

IF R SAYS GOVT HELP FOR PEOPLE TO PAY FOR HEALTH CARE SHOULD INCREASE /
IF R SAYS GOVT HELP FOR PEOPLE TO PAY FOR HEALTH CARE SHOULD DECREASE:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242351 or V242352
-1. Inapplicable
1. Increase a great deal
2. Increase a moderate amount
3. Increase a little
4. No change
5. Decrease a little
6. Decrease a moderate amount
7. Decrease a lot

Survey Question(s)

ECONEQ_GOVHLTHHLP, ECONEQ_GOVHLTHHLPAMT

Question

Now for questions on different topics. Do the health benefits of vaccinations generally outweigh the risks, do the risks outweigh the benefits, or is there no difference?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Benefits outweigh risks
2. Risks outweigh benefits
3. No difference

Survey Question(s)

VACCINE2_RISKS

Question

Are the health benefits of vaccinations [much greater, moderately greater, or slightly greater / slightly greater, moderately greater, or much greater]? / Are the risks of vaccinations [much greater, moderately greater, or slightly greater / slightly greater, moderately greater, or much greater]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much greater
2. Moderately greater
3. Slightly greater

Survey Question(s)

VACCINE2_RISKSSTR

Universe

IF R SAYS HEALTH BENEFITS OF VACCINES OUTWEIGH RISKS /
IF R SAYS HEALTH RISKS OF VACCINES OUTWEIGHT BENEFITS:

Response Order

Forward/Reverse order

Question

Do the health benefits of vaccinations generally outweigh the risks, do the risks outweigh the benefits, or is there no difference?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Benefits greatly outweigh risks
2. Benefits moderately outweigh risks
3. Benefits slightly outweigh risks
4. No difference
5. Risks slightly outweigh benefits
6. Risks moderately outweigh benefits
7. Risks greatly outweigh benefits

Survey Question(s)

PAPI POST Q91

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242354 or V242355
-1. Inapplicable
1. Benefits greatly outweigh risks
2. Benefits moderately outweigh risks
3. Benefits slightly outweigh risks
4. No difference
5. Risks slightly outweigh benefits
6. Risks moderately outweigh benefits
7. Risks greatly outweigh benefits

Survey Question(s)

VACCINE2_RISKS, VACCINE2_RISKSSTR, PAPI POST Q91

Question

Do you think attention to sexual harassment [has gone too far, has not gone far enough, or has been about right / has been about right, has not gone far enough, or has gone too far]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Has gone too far
2. Has not gone far enough
3. Has been about right

Survey Question(s)

HARASS_ATTN

Response Order

Forward/Reverse order

Question

Has it gone [much too far or a little too far / a little too far or much too far]?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much too far
2. A little too far

Survey Question(s)

HARASS_ATTNFAR

Universe

IF R THINKS ATTENTION HAS GONE TOO FAR:

Response Order

Forward/Reverse order

Question

Has it [not gone nearly far enough or not gone quite far enough / not gone quite far enough or not gone nearly far enough]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not nearly far enough
2. Not quite far enough

Survey Question(s)

HARASS_ATTNNOTFAR

Universe

IF R THINKS ATTENTION HAS NOT GONE FAR ENOUGH:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242358, V242359, V242360
-1. Inapplicable
1. Much too far
2. A little too far
3. Has been about right
4. Not quite far enough
5. Not nearly far enough

Survey Question(s)

HARASS_ATTN, HARASS_ATTNFAR, HARASS_ATTNNOTFAR

Question

Do you favor, oppose, or neither favor nor oppose allowing transgender people to serve in the United States Armed Forces?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Favor
2. Oppose
3. Neither favor nor oppose

Survey Question(s)

TRANSMIL_ALLOWMIL

Question

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A moderate amount
3. A little

Survey Question(s)

TRANSMIL_ALLOWMILSTR

Universe

IF R ALLOWING TRANSGENDER PPL IN MILITARY/
IF R OPPOSES ALLOWING TRANSGENDER PPL IN MILITARY:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V241262 or V241263
-1. Inapplicable
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

TRANSMIL_ALLOWMIL, TRANSMIL_ALLOWMILSTR

Question

[Next, we’ll ask you the same question for several countries: How much is China a threat to the United States? / How much is China a threat to the United States?] [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. A moderate amount
4. A lot
5. A great deal

Survey Question(s)

FRGNTHRT_CHINA, PAPI POST Q97

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize order of all items in FRGNTHRT submodule: CHINA, RUSSIA, MEXICO, IRAN, JAPAN, ISRAEL

Response Order

Forward/Reverse order

Question

[Next, we’ll ask you the same question for several countries: How much is Russia a threat to the United States? / How much is Russia a threat to the United States?] [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

Survey Question(s)

FRGNTHRT_RUSSIA, PAPI POST Q98

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize order of all items in FRGNTHRT submodule: CHINA, RUSSIA, MEXICO, IRAN, JAPAN, ISRAEL

Response Order

Forward/Reverse order

Question

[Next, we’ll ask you the same question for several countries: How much is Mexico a threat to the United States? / How much is Mexico a threat to the United States?] [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

Survey Question(s)

FRGNTHRT_MEXICO

Randomization

Randomize order of all items in FRGNTHRT submodule: CHINA, RUSSIA, MEXICO, IRAN, JAPAN, ISRAEL

Response Order

Forward/Reverse order

Question

[Next, we’ll ask you the same question for several countries: How much is Iran a threat to the United States? / How much is Iran a threat to the United States?] [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

Survey Question(s)

FRGNTHRT_IRAN

Randomization

Randomize order of all items in FRGNTHRT submodule: CHINA, RUSSIA, MEXICO, IRAN, JAPAN, ISRAEL

Response Order

Forward/Reverse order

Question

[Next, we’ll ask you the same question for several countries: How much is Japan a threat to the United States? / How much is Japan a threat to the United States?] [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

Survey Question(s)

FRGNTHRT_JAPAN

Randomization

Randomize order of all items in FRGNTHRT submodule: CHINA, RUSSIA, MEXICO, IRAN, JAPAN, ISRAEL

Response Order

Forward/Reverse order

Question

[Next, we’ll ask you the same question for several countries: How much is Israel a threat to the United States? / How much is Israel a threat to the United States?] [Not at all, a little, a moderate amount, a lot, or a great deal / A great deal, a lot, a moderate amount, a little, or not at all]?

Value Labels

Survey Question(s)

FRGNTHRT_ISRAEL

Randomization

Randomize order of all items in FRGNTHRT submodule: CHINA, RUSSIA, MEXICO, IRAN, JAPAN, ISRAEL

Response Order

Forward/Reverse order

Question

How interested would you say you are in politics? Are you [very interested, somewhat interested, not very interested, or not at all interested / not at all interested, not very interested, somewhat interested, or very interested]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Very interested
2. Somewhat interested
3. Not very interested
4. Not at all interested

Survey Question(s)

CSES6_INTPOL, PAPI POST Q23

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

In the next questions, we would like to know what kind of media you used to follow news about parties and candidates during the recent election campaign. We begin with the traditional media of television, radio and newspapers, but regardless of whether you use these media in the traditional ways or online. During the recent election campaign, in a typical week, how many days did you:

Watch the news on a public television broadcaster?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. None/zero days
1. One day
2. Two days
3. Three days
4. Four days
5. Five days
6. Six days
7. Seven days

Survey Question(s)

CSES6_MEDIATVPUB

Question

(During the recent election campaign, in a typical week, how many days did you:)

Watch the news on cable television?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. None/zero days
1. One day
2. Two days
3. Three days
4. Four days
5. Five days
6. Six days
7. Seven days

Survey Question(s)

CSES6_MEDIATVPRIV

Question

(During the recent election campaign, in a typical week, how many days did you:)

Listen to the news on the radio?

Value Labels

Survey Question(s)

CSES6_MEDIARAD

Question

(During the recent election campaign, in a typical week, how many days did you:)

Read newspapers, regardless of whether you read them in print or online?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
0. None/zero days
1. One day
2. Two days
3. Three days
4. Four days
5. Five days
6. Six days
7. Seven days

Survey Question(s)

CSES6_MEDIAPAP, PAPI POST Q94

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

(During the recent election campaign, in a typical week, how many days did you:)

Visit online news sites?

Value Labels

Survey Question(s)

CSES6_MEDIAONL

Question

During the recent election campaign, in a typical week, how many days did you:

Use social media such as Facebook, Twitter or X, or Instagram to follow news about parties and candidates?

Value Labels

Survey Question(s)

CSES6_MEDIASOC

Question

And how often during a typical day did you use social media such as Facebook, Twitter or X, or Instagram to follow news about parties and candidates - only about once per day, several times per day, or at least ten times per day?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Only about once per day
2. Several times per day
3. At least ten times per day

Survey Question(s)

CSES6_MEDIASOCAMT

Universe

IF R SAYS SEVEN DAYS IN PREVIOUS ITEM:

Question

Please tell me whether you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree strongly / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree] with each of the following statements:

You feel you understand the most important political issues of this country.

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree strongly / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree]?)

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Strongly agree
2. Somewhat agree
3. Neither agree nor disagree
4. Somewhat disagree
5. Strongly disagree

Survey Question(s)

CSES6_UNDISS

Response Order

Forward/Reverse order

Question

‘Democracy is always and under all circumstances preferable to any other kind of government.’

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree]?)

Value Labels

Survey Question(s)

CSES6_PREFERDEM

Randomization

Randomize items PREFERDEM, COURTS, STRLEAD, REPWOMEN

Response Order

Forward/Reverse order

Question

‘The courts should be able to stop the government acting beyond its authority.’

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree] ?)

Value Labels

Survey Question(s)

CSES6_COURTS

Randomization

Randomize items PREFERDEM, COURTS, STRLEAD, REPWOMEN

Response Order

Forward/Reverse order

Question

‘Having a strong leader in government is good for the United States even if the leader bends the rules to get things done.’

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree]?)

Value Labels

Survey Question(s)

CSES6_STRLEAD

Randomization

Randomize items PREFERDEM, COURTS, STRLEAD, REPWOMEN

Response Order

Forward/Reverse order

Question

‘Policies to increase the representation of women in politics have gone too far.’

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree] ?)

Value Labels

Survey Question(s)

CSES6_REPWOMEN

Randomization

Randomize items PREFERDEM, COURTS, STRLEAD, REPWOMEN

Response Order

Forward/Reverse order

Question

‘Instead of elected politicians, the country would be run better if important political decisions were left up to: Successful business leaders.’

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree]?)

Value Labels

Survey Question(s)

CSES6_INSTEADBUS

Randomization

Randomize items INSTEADBUS, INSTEADEXP, INSTEADCIT

Response Order

Forward/Reverse order

Question

‘Instead of elected politicians, the country would be run better if important political decisions were left up to: Independent experts.’

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree]?)

Value Labels

Survey Question(s)

CSES6_INSTEADEXP

Randomization

Randomize items INSTEADBUS, INSTEADEXP, INSTEADCIT

Response Order

Forward/Reverse order

Question

‘Instead of elected politicians, the country would be run better if important political decisions were left up to: Citizens in referendums.’

(Do you [strongly agree, somewhat agree, neither agree nor disagree, somewhat disagree, or strongly disagree / strongly disagree, somewhat disagree, neither agree nor disagree, somewhat agree, or strongly agree]?)

Value Labels

Survey Question(s)

CSES6_INSTEADCIT

Randomization

Randomize items INSTEADBUS, INSTEADEXP, INSTEADCIT

Response Order

Forward/Reverse order

Question

On a scale of 0 to 10, where 0 means the United States is not at all democratic, and 10 means the United States is completely democratic, what position would you choose?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
00. Not at all democratic
10. Completely democratic

Survey Question(s)

CSES6_DEMOCRATIC

Question

How about:

Congress?

Do you trust it a lot, trust it somewhat, do not trust it very much, or do not trust it at all?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Trust a lot
2. Trust somewhat
3. Do not trust very much
4. Do not trust at all

Survey Question(s)

CSES6_TRUSTCONG

Randomization

Randomize items TRUSTCONG, TRUSTGOV, TRUSTJUD, TRUSTSCI, TRUSTPARTIES, TRUSTMEDIA, TRUSTSOCMEDIA

Question

(How about:)

The government?

(Do you trust it a lot, trust it somewhat, do not trust it very much, or do not trust it at all?)

Value Labels

Survey Question(s)

CSES6_TRUSTGOV

Randomization

Randomize items TRUSTCONG, TRUSTGOV, TRUSTJUD, TRUSTSCI, TRUSTPARTIES, TRUSTMEDIA, TRUSTSOCMEDIA

Question

(How about:)

The judiciary?

(Do you trust it a lot, trust it somewhat, do not trust it very much, or do not trust it at all?)

Value Labels

Survey Question(s)

CSES6_TRUSTJUD

Randomization

Randomize items TRUSTCONG, TRUSTGOV, TRUSTJUD, TRUSTSCI, TRUSTPARTIES, TRUSTMEDIA, TRUSTSOCMEDIA

Question

(How about:)

Scientists?

(Do you trust them a lot, trust them somewhat, do not trust them very much, or do not trust them at all?)

Value Labels

Survey Question(s)

CSES6_TRUSTSCI

Randomization

Randomize items TRUSTCONG, TRUSTGOV, TRUSTJUD, TRUSTSCI, TRUSTPARTIES, TRUSTMEDIA, TRUSTSOCMEDIA

Question

(How about:)

The political parties?

(Do you trust them a lot, trust them somewhat, do not trust them very much, or do not trust them at all?)

Value Labels

Survey Question(s)

CSES6_TRUSTPARTIES

Randomization

Randomize items TRUSTCONG, TRUSTGOV, TRUSTJUD, TRUSTSCI, TRUSTPARTIES, TRUSTMEDIA, TRUSTSOCMEDIA

Question

(How about:)

Traditional news media, such as newspapers, television or radio?

(Do you trust them a lot, trust them somewhat, do not trust them very much, or do not trust them at all?)

Value Labels

Survey Question(s)

CSES6_TRUSTMEDIA, PAPI POST Q93

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Randomization

Randomize items TRUSTCONG, TRUSTGOV, TRUSTJUD, TRUSTSCI, TRUSTPARTIES, TRUSTMEDIA, TRUSTSOCMEDIA

Question

(How about:)

Social media, such as Facebook, Twitter or X, or Instagram?

(Do you trust them a lot, trust them somewhat, do not trust them very much, or do not trust them at all?)

Value Labels

Survey Question(s)

CSES6_TRUSTSOCMEDIA

Randomization

Randomize items TRUSTCONG, TRUSTGOV, TRUSTJUD, TRUSTSCI, TRUSTPARTIES, TRUSTMEDIA, TRUSTSOCMEDIA

Question

Now thinking about the performance of the president in general, how good or bad a job do you think the president in Washington did over the past 4 years? [Has he done a very good job? A good job? A bad job? A very bad job? / Has he done a very bad job? A bad job? A good job? A very good job?]

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very good job
2. Good job
3. Bad job
4. Very bad job

Survey Question(s)

CSES6_PRESPERF

Response Order

Forward/Reverse order

Question

And how good or bad a job do you think the president in Washington has done over the past 4 years in handling the consequences of the coronavirus pandemic? [Has he done a very good job? A good job? A bad job? A very bad job? / Has he done a very bad job? A bad job? A good job? A very good job?]

Value Labels

Survey Question(s)

CSES6_PRESCOVID

Response Order

Forward/Reverse order

Question

Would you say that over the past twelve months, the state of the economy in the United States has [gotten much better, gotten somewhat better, stayed about the same, gotten somewhat worse, or gotten much worse / gotten much worse, gotten somewhat worse, stayed about the same, gotten somewhat better, or gotten much better]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Gotten much better
2. Gotten somewhat better
3. Stayed about the same
4. Gotten somewhat worse
5. Gotten much worse

Survey Question(s)

CSES6_ECON, PAPI POST Q95

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Are you [very satisfied, fairly satisfied, not very satisfied, or not at all satisfied / not at all satisfied, not very satisfied, fairly satisfied, or very satisfied] with your decision to vote for the party/candidate you voted for in the last election?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very satisfied
2. Fairly satisfied
4. Not very satisfied
5. Not at all satisfied

Survey Question(s)

CSES6_VOTESAT

Universe

IF R VOTED:

Response Order

Forward/Reverse order

Question

Value Labels

Survey Question(s)

CSES6_NOVOTE

Universe

IF R DID NOT VOTE:

Response Order

Forward/Reverse order

Question

Are you [very satisfied, fairly satisfied, not very satisfied, or not at all satisfied / not at all satisfied, not very satisfied, fairly satisfied, or very satisfied] with the variety of choice in the election?

Value Labels

Survey Question(s)

CSES6_ELECTCHOICE

Response Order

Forward/Reverse order

Question

In some countries, people believe that the elections are conducted fairly. In other countries, people believe that elections are
conducted unfairly.

Thinking of the election that just occured in the United States, where would you place it on a scale of one to five where ONE means that the election was conducted fairly and FIVE means that the election was conducted unfairly?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Election was conducted fairly
5. Election was conducted unfairly

Survey Question(s)

CSES6_FAIRELECT, PAPI POST Q66

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Some people say that no matter who people vote for, it won’t make any difference to what happens. Others say that who people vote for can make a big difference to what happens. Using the scale in the booklet, where ONE means that voting won’t make any difference to what happens and FIVE means that voting can make a big difference, where would you place yourself?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Who people vote for won’t make any difference
5. Who people vote for can make a big difference

Survey Question(s)

CSES6_VOTEDIFF

Question

I’d like to know what you think about each of our political parties. After I read the name of a political party, please rate it on a scale from 0 to 10, where 0 means you strongly dislike that party and 10 means that you strongly like that party. If I come to a party you haven’t heard of or you feel you do not know enough about, just say so.

The first party is: the Democratic Party

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
00. Strongly dislike
10. Strongly like
96. Haven’t heard of party
97. Do not know enough about party
98. Refused {VOL}

Survey Question(s)

CSES6_LDDEMPTY

Question

Using the same scale, where would you place: the Republican Party

Value Labels

Survey Question(s)

CSES6_LDREPPTY

Question

Using the same scale, where would you place: Kamala Harris

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
00. Strongly dislike
10. Strongly like
97. Do not know enough about candidate
98. Refused {VOL}

Survey Question(s)

CSES6_LDDPC

Question

Using the same scale, where would you place: Donald Trump

Value Labels

Survey Question(s)

CSES6_LDRPC

Question

In politics people sometimes talk of left and right. Where would you place the Democratic Party on a scale from 0 to 10 where 0 means the left and 10 means the right?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Left
10. Right
95. Haven’t heard of left-right
96. Do not know enough about party
97. Refused
98. Don’t know where to place

Survey Question(s)

CSES6_LRDPC

Question

Using the same scale, where would you place the Republican Party?

Value Labels

Survey Question(s)

CSES6_LRRPC

Question

Where would you place yourself on this scale?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Left
10. Right

Survey Question(s)

CSES6_LRSELF

Question

On the whole, are you [very satisfied, fairly satisfied, not very satisfied, or not at all satisfied / not at all satisfied, not very satisfied, fairly satisfied, or very satisfied] with the way democracy works in the United States?

Value Labels

Survey Question(s)

CSES6_DEMSATIS

Response Order

Forward/Reverse order

Question

Do you usually think of yourself as close to any particular party?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
5. No

Survey Question(s)

CSES6_PTYCLOSE

Question

Do you feel yourself a little closer to one of the political parties than the others?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
5. No

Survey Question(s)

CSES6_PTYLIT

Universe

IF R DOES NOT FEEL CLOSE TO ANY PARTICULAR PARTY:

Question

Which party do you feel closest to?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Democratic
3. Republican
7. Other {SPECIFY}

Survey Question(s)

CSES6_WHPTY

Universe

IF R FEELS CLOSE TO ANY PARTICULAR PARTY:

Question

Do you feel [very close to this party, somewhat close, or not very close/ not very close to this party, somewhat close, or very close]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very close
2. Somewhat close
3. Not very close

Survey Question(s)

CSES6_HOWCLOSE

Universe

IF R HAS NAMED A PARTY TO WHICH HE/SHE FEELS CLOSEST:

Response Order

Forward/Reverse order

Question

The current percentage of women in congress after the most recent election is [PERCENTAGE] percent. Thinking about this percentage, would you say that it is too high, too low, or about right?”

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too high
2. Too low
3. About right

Survey Question(s)

CSES6_PWOMEN

Question

Who is better suited to lead the country during a public health crisis: always male political leaders, usually male political leaders, usually female political leaders, always female political leaders, or both equally?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Always male political leaders
2. Usually male political leaders
3. Usually female political leaders
4. Always female political leaders
5. Both equally

Survey Question(s)

CSES6_GENDPUBHLT

Randomization

Randomize order of items GENDPUBHLT, GENDECON

Question

Who is better suited to lead the country during an economic crisis: always male political leaders, usually male political leaders, usually female political leaders, always female political leaders, or both equally?

Value Labels

Survey Question(s)

CSES6_GENDECON

Randomization

Randomize order of items GENDPUBHLT, GENDECON

Question

How fairly or not do you think that all groups in society are treated in the United States: [very fairly, quite fairly, not very fairly, or not at all fairly / not at all fairly, not very fairly, quite fairly, or very fairly]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very fairly
2. Quite fairly
3. Not very fairly
4. Not at all fairly

Survey Question(s)

CSES6_GRPTREAT

Response Order

Forward/Reverse order

Question

How well do you think that our political system guarantees adequate healthcare for all citizens: [very well, quite well, not very well, or not well at all / not well at all, not very well, quite well or very well]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very well
2. Quite well
3. Not very well
4. Not well at all

Survey Question(s)

CSES6_HEALTH

Response Order

Forward/Reverse order

Question

How did the coronavirus pandemic affect how united society is in the United States: [very positively, fairly positively, not at all, fairly negatively or very negatively / very negatively, fairly negatively, not at all, fairly positively, or very positively]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very positively
2. Fairly positively
3. Not at all
4. Fairly negatively
5. Very negatively

Survey Question(s)

CSES6_COVIDUNITED

Response Order

Forward/Reverse order

Question

How did the coronavirus pandemic affect the functioning of democracy here in the United States: [very positively, fairly positively, not at all, fairly negatively or very negatively / very negatively, fairly negatively, not at all, fairly positively, or very positively]?

Value Labels

Survey Question(s)

CSES6_COVIDDEM

Response Order

Forward/Reverse order

Question

How has the coronavirus pandemic affected your personal economic situation: [very positively, fairly positively, not at all, fairly negatively or very negatively / very negatively, fairly negatively, not at all, fairly positively, or very positively]?

Value Labels

Survey Question(s)

CSES6_COVIDECON

Response Order

Forward/Reverse order

Question

To the best of your knowledge, have you or anyone living with you been infected with the coronavirus?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

CSES6_COVIDINFECT

Question

(Do you [agree strongly, agree somewhat, neither agree nor disagree, disagree somewhat, or disagree strongly /disagree strongly, disagree somewhat, neither agree nor disagree, agree somewhat, or agree strongly] with the following statement? )

‘Immigrants increase crime rates in the United States.’

Value Labels

Survey Question(s)

CSES6_IMMCRIME

Response Order

Forward/Reverse order

Question

Some people say that the following things are important for being truly American. Others says they are not important. How important do you think the following is for being truly American… [very important, fairly important, not very important, or not important at all / not important at all, not very important, fairly important, or very important]?

To have been born in the United States.

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Very important
2. Fairly important
3. Not very important
4. Not important at all

Survey Question(s)

CSES6_AMERBORN, PAPI POST Q103

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

(How important do you think the following is for being truly American: [very important, fairly important, not very important, or not important at all / not important at all, not very important, fairly important, or very important]?)

To be able to speak English.

Value Labels

Survey Question(s)

CSES6_AMERENG, PAPI POST Q104

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How widespread do you think corruption such as bribe taking is among politicians in the United States: [Very widespread, quite widespread, not very widespread, or it hardly happens at all / It hardly happens at all, is not very widespread, quite widespread, or very widespread]?

Value Labels

-9. Refused
-8. Don’t know
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very widespread
2. Quite widespread
3. Not very widespread
4. Hardly happens at all

Survey Question(s)

CSES6_POLCORRUPT, PAPI POST Q105

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

Several states have considered laws that would ban transgender girls from participating in K-12 girls’ sports. How much do you favor, oppose, or neither favor nor oppose such a law?

Value Labels

Survey Question(s)

PAPI POST Q92

Variable Note

Only PAPI respondents were asked this question in the post-election survey. All other modes received this question in the pre-election survey.

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V241373 or V241374
1. Favor a great deal
2. Favor a moderate amount
3. Favor a little
4. Neither favor nor oppose
5. Oppose a little
6. Oppose a moderate amount
7. Oppose a great deal

Survey Question(s)

TRANSPOLICY_TRANSPRT, TRANSPOLICY_TRANSPRTSTR, PAPI POST Q92

Question

How many guns do you or anyone else living here own? Write the number. If none, write 0.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable

Survey Question(s)

PAPI POST Q96

Variable Note

Only PAPI respondents were asked this question in the post-election survey. All other modes received this question in the pre-election survey.

Value Labels

-9. Refused
-2. Missing, pre-election breakoff or post-election no interview

Survey Question(s)

OWNGUN_GUNNUM, PAPI POST Q96

Question

What is your present religion, if any?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Protestant
2. Roman Catholic
3. Jewish
4. Muslim
5. Atheist
6. Agnostic
7. Something else
8. Nothing in particular

Survey Question(s)

PAPI POST Q100

Variable Note

PAPI respondents received a slightly altered version of the religion question in the post-election survey that other modes received in the pre-election survey.

Question

On another topic: Do you have any living sons or daughters of any age? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RCHILD_ANYCHILD

Question

On another topic: Do you have any living sons or daughters of any age? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RCHILD_ANYCHILD

Question

On another topic: Do you have any living sons or daughters of any age? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

RCHILD_ANYCHILD

Question

In the past four years, how much have political differences hurt your relationships with family members?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A lot
3. A moderate amount
4. A little
5. Not at all

Survey Question(s)

FAMPOL_DIFFHURT, PAPI POST Q99

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Response Order

Forward/Reverse order

Question

How often would you say that you have tender, concerned feelings for people from another racial or ethnic group who are less fortunate than you?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely often
2. Very often
3. Somewhat often
4. Not too often
5. Not often at all

Survey Question(s)

EMPATHY_CONCERN

Response Order

Forward/Reverse order

Question

How often would you say you try to better understand people of other racial or ethnic groups by imagining how things look from their perspective?

Value Labels

Survey Question(s)

EMPATHY_PERSP

Response Order

Forward/Reverse order

Question

Before criticizing somebody from another racial or ethnic group, how often do you try to imagine how you would feel if you were in their place?

Value Labels

Survey Question(s)

EMPATHY_PLACE

Response Order

Forward/Reverse order

Question

When you see someone being taken advantage of due to their race or ethnicity, how often do you feel protective towards them?

Value Labels

Survey Question(s)

EMPATHY_ADVANT

Response Order

Forward/Reverse order

Question

During the past 12 months, were you or any of your family members stopped or questioned by a police officer, or did this not happen in the past 12 months?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Was stopped or questioned in the past 12 months
2. Was not stopped or questioned in the past 12 months

Survey Question(s)

OWNPOLICE_STOPQUES

Question

Have you ever been arrested, or has that never happened to you?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Have been arrested
2. Never arrested

Survey Question(s)

OWNPOLICE_ARRESTED

Question

Among your immediate family members, relatives, neighbors, co-workers, or close friends, are any of them gay, lesbian, or bisexual as far as you know?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

KNOWLGBT_KNOWGAY

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELGAY

Universe

IF R HAS GAY FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELGAY

Universe

IF R HAS GAY FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELGAY

Universe

IF R HAS GAY FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELGAY

Universe

IF R HAS GAY FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELGAY

Universe

IF R HAS GAY FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELGAY

Universe

IF R HAS GAY FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

Among your immediate family members, relatives, neighbors, co-workers, or close friends, are any of them transgender as far as you know?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

KNOWLGBT_KNOWTRANS

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELTRANS

Universe

IF R HAS TRANSGENDER FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELTRANS

Universe

IF R HAS TRANSGENDER FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELTRANS

Universe

IF R HAS TRANSGENDER FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELTRANS

Universe

IF R HAS TRANSGENDER FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELTRANS

Universe

IF R HAS TRANSGENDER FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

What is your relationship to that person (or people)? (Mark any that apply)

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

KNOWLGBT_RELTRANS

Universe

IF R HAS TRANSGENDER FAMILY MEMBER, RELATIVE, NEIGHBOR, CO-WORKER, CLOSE FRIEND:

Question

Do you consider yourself a feminist, an anti-feminist, or neither of these?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Feminist
2. Anti-feminist
3. Neither

Survey Question(s)

FEMINISM_RFEMREV

Question

How important is it to you to be a feminist?

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely important
2. Very important
3. Somewhat important
4. A little important
5. Not at all important

Survey Question(s)

FEMINISM_IMPFEM

Universe

IF R CONSIDERS THEMSELF A FEMINIST:

Response Order

Forward/Reverse order

Question

[Using the same thermometer scale which you used earlier in the interview, how would you rate:
Asian-Americans

Please enter the rating number in the number box. Ratings between 50 degrees and 100 degrees mean that you feel favorable and warm toward the group. Ratings between 0 degrees and 50 degrees mean that you don’t feel favorable toward the group and that you don’t care too much for that group. You would rate the group at the 50 degree mark if you don’t feel particularly warm or cold toward the group.
/
How would you rate:
Asian-Americans]

TYPE THE NUMBER.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable

Survey Question(s)

THCASI_THGRASIAN, PAPI POST Q45

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF FIRST CASI THERMOMETER RATING /
IF NOT FIRST CASI THERMOMETER RATING:

Randomization

Order of CASI group thermometers

Question

[Using the same thermometer scale which you used earlier in the interview, how would you rate:
Hispanics

Please enter the rating number in the number box. Ratings between 50 degrees and 100 degrees mean that you feel favorable and warm toward the group. Ratings between 0 degrees and 50 degrees mean that you don’t feel favorable toward the group and that you don’t care too much for that group. You would rate the group at the 50 degree mark if you don’t feel particularly warm or cold toward the group.
/
How would you rate:
Hispanics]

TYPE THE NUMBER.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable

Survey Question(s)

THCASI_THGRHISP, PAPI POST Q46

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF FIRST CASI THERMOMETER RATING /
IF NOT FIRST CASI THERMOMETER RATING:

Randomization

Order of CASI group thermometers

Question

[Using the same thermometer scale which you used earlier in the interview, how would you rate:
blacks

Please enter the rating number in the number box. Ratings between 50 degrees and 100 degrees mean that you feel favorable and warm toward the group. Ratings between 0 degrees and 50 degrees mean that you don’t feel favorable toward the group and that you don’t care too much for that group. You would rate the group at the 50 degree mark if you don’t feel particularly warm or cold toward the group.
/
How would you rate:
blacks]

TYPE THE NUMBER.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable

Survey Question(s)

THCASI_THGRBLACK, PAPI POST Q44

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF FIRST CASI THERMOMETER RATING /
IF NOT FIRST CASI THERMOMETER RATING:

Randomization

Order of CASI group thermometers

Question

[Using the same thermometer scale which you used earlier in the interview, how would you rate:
illegal immigrants

Please enter the rating number in the number box. Ratings between 50 degrees and 100 degrees mean that you feel favorable and warm toward the group. Ratings between 0 degrees and 50 degrees mean that you don’t feel favorable toward the group and that you don’t care too much for that group. You would rate the group at the 50 degree mark if you don’t feel particularly warm or cold toward the group.
/
How would you rate:
illegal immigrants]

TYPE THE NUMBER.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable

Survey Question(s)

THCASI_THGRILLEG, PAPI POST Q53

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF FIRST CASI THERMOMETER RATING /
IF NOT FIRST CASI THERMOMETER RATING:

Randomization

Order of CASI group thermometers

Question

[Using the same thermometer scale which you used earlier in the interview, how would you rate:
whites

Please enter the rating number in the number box. Ratings between 50 degrees and 100 degrees mean that you feel favorable and warm toward the group. Ratings between 0 degrees and 50 degrees mean that you don’t feel favorable toward the group and that you don’t care too much for that group. You would rate the group at the 50 degree mark if you don’t feel particularly warm or cold toward the group.
/
How would you rate:
whites]

TYPE THE NUMBER.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable

Survey Question(s)

THCASI_THGRWHITE, PAPI POST Q43

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Universe

IF FIRST CASI THERMOMETER RATING /
IF NOT FIRST CASI THERMOMETER RATING:

Randomization

Order of CASI group thermometers

Question

How likely is it that many whites are unable to find a job because employers are hiring minorities instead?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Extremely likely
2. Very likely
3. Moderately likely
4. Slightly likely
5. Not at all likely

Survey Question(s)

GRPCONSC_WHITEJOB

Response Order

Forward/Reverse order

Question

In general, does the federal government [treat whites better than blacks, treat them both same, or treat blacks better than whites / treat blacks better than whites, treat them both the same, or treat whites better than blacks]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Treat whites better
2. Treat both the same
3. Treat blacks better

Survey Question(s)

TREATBLACK_DISCFED

Response Order

Forward/Reverse order

Question

Does the federal government treat whites [much better, moderately better, or a little better / a little better, moderately better, or much better]? / Does the federal government treat blacks [much better, moderately better, or a little better / a little better, moderately better, or much better]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much
2. Moderately
3. A little

Survey Question(s)

TREATBLACK_DISCFEDAMT

Universe

IF R SAYS FEDERAL GOVT TREATS WHITES BETTER THAN BLACKS /
IF R SAYS FEDERAL GOVT TREATS BLACKS BETTER THAN WHITES:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242520 or V242521
-1. Inapplicable
1. Treat whites much better
2. Treat whites moderately better
3. Treats whites a little better
4. Treats both the same
5. Treat blacks a little better
6. Treat blacks moderately better
7. Treat blacks much better

Survey Question(s)

TREATBLACK_DISCFED, TREATBLACK_DISCFEDAMT

Question

In general, do the police [treat whites better than blacks, treat them both same, or treat blacks better than whites / treat blacks better than whites, treat them both the same, or treat whites better than blacks]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Treat whites better
2. Treat both the same
3. Treat blacks better

Survey Question(s)

TREATBLACK_DISCPOLICE

Response Order

Forward/Reverse order

Question

Do the police treat whites [much better, moderately better, or a little better / a little better, moderately better, or much better]? / Do the police treat blacks [much better, moderately better, or a little better / a little better, moderately better, or much better]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Much
2. Moderately
3. A little

Survey Question(s)

TREATBLACK_DISCPOLICEAMT

Universe

IF R SAYS POLICE TREAT WHITES BETTER THAN BLACKS /
IF R SAYS POLICE TREAT BLACKS BETTER THAN WHITES:

Response Order

Forward/Reverse order

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. DK/RF in V242523 or V242524
-1. Inapplicable
1. Treat whites much better
2. Treat whites moderately better
3. Treats whites a little better
4. Treats both the same
5. Treat blacks a little better
6. Treat blacks moderately better
7. Treat blacks much better

Survey Question(s)

TREATBLACK_DISCPOLICE, TREATBLACK_DISCPOLICEAMT

Question

Would you say that whites have [too much influence in American politics, just about the right amount of influence in American politics, or too little influence in American politics / too little influence in American politics, just about the right amount of influence in American politics, or too much influence in American politics]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much influence
2. Just about the right amount of influence
3. Too little influence

Survey Question(s)

RACEGENPO_INFLWHITE

Response Order

Forward/Reverse order

Question

Would you say that blacks have [too much influence in American politics, just about the right amount of influence in American politics, or too little influence in American politics / too little influence in American politics, just about the right amount of influence in American politics, or too much influence in American politics]?

Value Labels

Survey Question(s)

RACEGENPO_INFLBLACKS

Response Order

Forward/Reverse order

Question

Would you say that Hispanics have [too much influence in American politics, just about the right amount of influence in American politics, or too little influence in American politics / too little influence in American politics, just about the right amount of influence in American politics, or too much influence in American politics]?

Value Labels

Survey Question(s)

RACEGENPO_INFLHISP

Response Order

Forward/Reverse order

Question

Would you say that Asians [too much influence in American politics, just about the right amount of influence in American politics, or too little influence in American politics / too little influence in American politics, just about the right amount of influence in American politics, or too much influence in American politics]?

Value Labels

Survey Question(s)

RACEGENPO_INFLAS

Response Order

Forward/Reverse order

Question

How important is being Hispanic to your identity?

Value Labels

Survey Question(s)

IDENT_HISPID

Universe

IF R IDENTIFIED AS HISPANIC IN THE PRE:

Response Order

Forward/Reverse order

Variable Note

Data of this previously restricted variable were restored for the full release version (20260519) of the 2024 Time Series data.

Question

How important is being white to your identity?

Value Labels

Survey Question(s)

IDENT_WHITEID

Universe

IF R MENTIONS WHITE IN PRE RACE SELF-IDENTIFICATION:

Response Order

Forward/Reverse order

Variable Note

Data of this previously restricted variable were restored for the full release version (20260519) of the 2024 Time Series data.

Question

How important is being black or African-American to your identity?

Value Labels

Survey Question(s)

IDENT_BLACKID

Universe

IF R MENTIONS BLACK IN PRE RACE SELF-IDENTIFICATION:

Response Order

Forward/Reverse order

Variable Note

Data of this previously restricted variable were restored for the full release version (20260519) of the 2024 Time Series data.

Question

How important is being American Indian or Alaska Native to your identity?

Value Labels

Survey Question(s)

IDENT_NATIVEID

Universe

IF R MENTIONS NATIVE AMERICAN IN PRE RACE SELF-IDENTIFICATION:

Response Order

Forward/Reverse order

Variable Note

Data of this previously restricted variable were restored for the full release version (20260519) of the 2024 Time Series data.

Question

How important is being Asian to your identity?

Value Labels

Survey Question(s)

IDENT_ASIANID

Universe

IF R MENTIONS ASIAN IN PRE RACE SELF-IDENTIFICATION:

Response Order

Forward/Reverse order

Variable Note

Data of this previously restricted variable were restored for the full release version (20260519) of the 2024 Time Series data.

Question

How important is being Native Hawaiian or other Pacific Islander to your identity?

Value Labels

Survey Question(s)

IDENT_PACIFID

Universe

IF R MENTIONS NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER IN PRE RACE SELF-
IDENTIFICATION:

Response Order

Forward/Reverse order

Variable Note

Data of this previously restricted variable were restored for the full release version (20260519) of the 2024 Time Series data.

Question

How important is being American to your identity?

Value Labels

Survey Question(s)

IDENT_AMERID

Response Order

Forward/Reverse order

Question

How much do you think that what happens generally to white people in this country will affect what happens in your life? [A lot, some, not very much, or not at all / Not at all, not very much, some, or a lot]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A lot
2. Some
3. Not very much
4. Not at all

Survey Question(s)

LINK_AFFWHITES

Universe

IF R IS IDENTIFIED AS WHITE IN PRE-ELECTION INTERVIEW:

Response Order

Forward/Reverse order

Question

How much do you think that what happens generally to Hispanic people in this country will affect what happens in your life? [A lot, some, not very much, or not at all / Not at all, not very much, some, or a lot]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A lot
2. Some
3. Not very much
4. Not at all

Survey Question(s)

LINK_AFFHISP

Universe

IF R IS IDENTIFIED AS HISPANIC IN PRE-ELECTION INTERVIEW:

Response Order

Forward/Reverse order

Question

How much do you think that what happens generally to black people in this country will affect what happens in your life? [A lot, some, not very much, or not at all / Not at all, not very much, some, or a lot]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A lot
2. Some
3. Not very much
4. Not at all

Survey Question(s)

LINK_AFFBLACKS

Universe

IF R IS IDENTIFIED AS BLACK OR AFRICAN-AMERICAN IN PRE-ELECTION INTERVIEW:

Response Order

Forward/Reverse order

Question

How much do you think that what happens generally to Asian people in this country will affect what happens in your life? [A lot, some, not very much, or not at all / Not at all, not very much, some, or a lot]?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A lot
2. Some
3. Not very much
4. Not at all

Survey Question(s)

LINK_AFFASIAN

Universe

IF R IS IDENTIFIED AS ASIAN IN PRE-ELECTION INTERVIEW:

Response Order

Forward/Reverse order

Question

Where would you rate whites in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Hard-working
7. Lazy

Survey Question(s)

STYPEPO_HWKWHITE

Question

Where would you rate blacks in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Hard-working
7. Lazy

Survey Question(s)

STYPEPO_HWKBLACK

Randomization

Order of hardworking stereotype groups after Whites

Question

Where would you rate Hispanics in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Hard-working
7. Lazy

Survey Question(s)

STYPEPO_HWKHISPREV

Randomization

Order of hardworking stereotype groups after Whites

Question

Where would you rate Asian-Americans in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Hard-working
7. Lazy

Survey Question(s)

STYPEPO_HWKASIAN

Randomization

Order of hardworking stereotype groups after Whites

Question

Where would you rate whites in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Peaceful
7. Violent

Survey Question(s)

STYPEPO_VIOLWHITE

Question

Where would you rate blacks in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Peaceful
7. Violent

Survey Question(s)

STYPEPO_VIOLBLACK

Randomization

Order of peaceful stereotype groups after Whites

Question

Where would you rate Hispanics in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Peaceful
7. Violent

Survey Question(s)

STYPEPO_VIOLHISPREV

Randomization

Order of peaceful stereotype groups after Whites

Question

Where would you rate Asian-Americans in general on this scale?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Peaceful
7. Violent

Survey Question(s)

STYPEPO_VIOLASIAN

Randomization

Order of peaceful stereotype groups after Whites

Question

How much discrimination is there in the United States today against each of the following groups?
Blacks

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. A lot
3. A moderate amount
4. A little
5. None at all

Survey Question(s)

DISCRIM_DISCBLCK

Randomization

Items divided into two groups to display in two grids. Order of items in each grid randomized. Group 1: DISCBLCK, DISCHISP, DISCASIAN, DISCWHT, DISCMUSL, DISCTIAN; Group 2: DISCGAY, DISCWOM, DISCMEN, DISCTRANS.

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Hispanics

Value Labels

Survey Question(s)

DISCRIM_DISCHISP

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Asians

Value Labels

Survey Question(s)

DISCRIM_DISCASIAN

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Whites

Value Labels

Survey Question(s)

DISCRIM_DISCWHT

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Gays and Lesbians

Value Labels

Survey Question(s)

DISCRIM_DISCGAY

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Women

Value Labels

Survey Question(s)

DISCRIM_DISCWOM

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Men

Value Labels

Survey Question(s)

DISCRIM_DISCMEN

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Muslims

Value Labels

Survey Question(s)

DISCRIM_DISCMUSL

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Christians

Value Labels

Survey Question(s)

DISCRIM_DISCXTIAN

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination is there in the United States today against each of the following groups?
Transgender people

Value Labels

Survey Question(s)

DISCRIM_DISCTRANS

Randomization

Response Order

Forward/Reverse order

Question

How much discrimination have you personally faced because of your ethnicity or race?

Value Labels

Survey Question(s)

DISCRIM_DISCPERS

Response Order

Forward/Reverse order

Question

Have you ever personally experienced sexual harassment at work, or not?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Have
2. Have not

Survey Question(s)

DISCRIM_SEXHARASS

Question

How often have you personally experienced sexual harassment at work?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-2. Missing due to data correction; see codebook note
-1. Inapplicable
1. Once
2. A few times
3. Many times

Survey Question(s)

DISCRIM_SEXHARASSAMT

Universe

IF R EXPERIENCED SEXUAL HARASSMENT AT WORK:

Question

Now we have a few questions about issues in the news recently.

What was the current unemployment rate in the United States as of November 1, 2024 – 2.1%, 4.1%, 6.1%, or 8.1%?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. 2.1%
2. 4.1%
3. 6.1%
4. 8.1%

Survey Question(s)

KNOWL_EMPRATE

Question

Which of these two statements do you think is most likely to be true?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Most scientific evidence shows childhood vaccines cause autism
2. Most scientific evidence shows childhood vaccines do not cause autism

Survey Question(s)

MISINFO_AUTISM

Question

How confident are you about that?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

MISINFO_AUTISMCONF

Universe

IF R THINKS VACCINES CAUSE AUTISM /
IF R DOES NOT THINK VACCINES CAUSE AUTISM:

Response Order

Forward/Reverse order

Question

Which of these two statements do you think is most likely to be true?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. World temperatures have risen on average over the last 100 years
2. World temperatures have not risen on average over the last 100 years.

Survey Question(s)

MISINFO_WARM

Question

How confident are you about that?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

MISINFO_WARMCONF

Universe

IF R THINKS WORLD TEMPERATURES ARE RISING IN LAST 100 YEARS /
IF R DOES NOT THINK WORLD TEMPERATURES ARE RISING IN LAST 100 YEARS

Response Order

Forward/Reverse order

Question

Which of these two statements do you think is most likely to be true?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Donald Trump was the legitimate winner of the 2020 presidential election
2. Joe Biden was the legitimate winner of the 2020 presidential election

Survey Question(s)

MISINFO_WIN20

Question

How confident are you about that?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

MISINFO_WIN20CONF

Universe

IF R THINKS TRUMP WAS LEGITIMATE WINNER OF 2020 ELECTION /
IF R THINKS BIDEN WAS LEGITIMATE WINNER OF 2020 ELECTION:

Response Order

Forward/Reverse order

Question

Which of these two statements do you think is most likely to be true?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Hunter Biden’s laptop showed that he made deals with Ukrainian and Chinese businesses
2. Hunter Biden’s laptop did not show that he made deals with Ukrainian and Chinese businesses

Survey Question(s)

MISINFO_HUNTER

Question

How confident are you about that?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

MISINFO_HUNTERCONF

Universe

IF R THINKS HUNTER BIDEN’S LAPTOP SHOWED BUSINESS DEALS /
IF R THINKS HUNTER BIDEN’S LAPTOP DID NOT SHOW BUSINESS DEALS:

Response Order

Forward/Reverse order

Question

Which of these two statements do you think is most likely to be true?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. The events on January 6, 2021 were planned and carried out by pro-Trump protesters
2. The events on January 6, 2021 were planned and carried out by FBI agents posing as pro-Trump protesters

Survey Question(s)

MISINFO_JANSIX

Question

How confident are you about that?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

MISINFO_JANSIXCONF

Universe

IF R THINKS EVENTS ON JANUARY 6, 2021 WERE PLANNED AND CARRIED OUT BY PRO-TRUMP PROTESTORS /
IF R THINKS EVENTS ON JANUARY 6, 2021 WERE PLANNED AND CARRIED OUT BY FBI POSING AS PRO-TRUMP PROTESTORS:

Response Order

Forward/Reverse order

Question

Which of these two statements do you think is most likely to be true?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Donald Trump’s campaign colluded with the Russian government in 2016
2. Donald Trump’s campaign did not collude with the Russian government in 2016

Survey Question(s)

MISINFO_TRUMP16

Question

How confident are you about that?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

MISINFO_TRUMP16CONF

Universe

IF R THINKS TRUMP’S CAMPAIGN COLLUDED WITH RUSSIA IN 2016 /
IF R THINKS TRUMP’S CAMPAIGN DID NOT COLLUDE WITH RUSSIA IN 2016:

Response Order

Forward/Reverse order

Question

Which of these two statements do you think is most likely to be true?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Donald Trump was the legitimate winner of the 2024 presidential election
2. Kamala Harris was the legitimate winner of the 2024 presidential election

Survey Question(s)

MISINFO_WIN24

Question

How confident are you about that?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Not at all
2. A little
3. Moderately
4. Very
5. Extremely

Survey Question(s)

MISINFO_WIN24CONF

Universe

IF R THINKS DONALD TRUMP WAS LEGITIMATE WINNER OF ELECTION IN 2024 /
IF R THINKS KAMALA HARRIS WAS LEGITIMATE WINNER OF ELECTION IN 2024:

Response Order

Forward/Reverse order

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE, PAPI POST Q101

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE

Question

Which social media apps or websites have you visited in the past year? Mark all that apply.

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

SOCMEDIA_SOCMEDTYPE

Question

How often do you use Facebook?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Many times every day
2. A few times every day
3. About once a day
4. A few times each week
5. About once a week
6. Once or twice a month
7. Less than once a month

Survey Question(s)

SOCMEDIA_FBFREQ

Universe

IF R HAS VISITED FACEBOOK IN PAST YEAR:

Question

When using Facebook, how often do you post information about political issues or candidates?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Always
2. Most of the time
3. About half of the time
4. Sometimes
5. Never

Survey Question(s)

SOCMEDIA_FBPOSTPOL

Universe

IF R HAS VISITED FACEBOOK IN PAST YEAR:

Response Order

Forward/Reverse order

Question

How often do you use X, formerly known as Twitter?

Value Labels

Survey Question(s)

SOCMEDIA_TWITFREQ

Universe

IF R HAS VISITED X IN PAST YEAR:

Question

When using X, formerly known as Twitter, how often do you post information about political issues or candidates?

Value Labels

Survey Question(s)

SOCMEDIA_TWITPOSTPOL

Universe

IF R HAS VISITED X IN PAST YEAR:

Response Order

Forward/Reverse order

Question

[(STATE)’s public records say (one person is/NUMBER people are/these five people are) registered to vote at (SAMPLED ADDRESS) / We found the following voter (record/records) resembling you or linked to your address.]

Does (this record/one of these) describe you, even if some information is not correct?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. I am person 1
2. I am person 2
3. I am person 3
4. I am person 4
5. I am person 5
6. My information is not here

Survey Question(s)

VOTEVAL_LIST

Universe

IF R IS NOT IN GSS SAMPLE:
IF FTF TYPE IS IN-PERSON AND NOT VIDEO OR PHONE:
IF MATCHES FOUND AT 1 ADDRESS /
IF MATCHES FOUND AT MORE THAN ONE ADDRESS:

Question

Is this information correct and complete for you, or is there an error?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. My name, gender, birth date, and address are correct
2. There is an error

Survey Question(s)

VOTEVAL_CORRECT1

Universe

IF R IS PERSON 1, 2, 3, 4, OR 5:

Question

Please type the correct information for you in the spaces below. When all the information is correct, please click Next.

Value Labels

-3. RESTRICTED

Survey Question(s)

VOTEVAL_CORRECT2

Universe

IF R SAYS THERE IS AN ERROR:

Question

How comfortable or uncomfortable are you being asked about this voter registration information?

Any comments about this topic?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very comfortable
2. Moderately comfortable
3. Slightly comfortable
4. Neither comfortable nor uncomfortable
5. Slightly uncomfortable
6. Moderately uncomfortable
7. Very uncomfortable [TEXT BOX]

Survey Question(s)

VOTEVAL_FEEDBACK

Universe

IF R IS NOT IN GSS SAMPLE:
IF FTF TYPE IS IN-PERSON AND NOT VIDEO OR PHONE:
IF MATCHES FOUND AT 1 ADDRESS /
IF MATCHES FOUND AT MORE THAN ONE ADDRESS:

Question

How comfortable or uncomfortable are you being asked about this voter registration information?

Any comments about this topic?

Value Labels

-2. Additional comments available in separate file

Survey Question(s)

VOTEVAL_FEEDBACK

Universe

IF R IS NOT IN GSS SAMPLE:
IF FTF TYPE IS IN-PERSON AND NOT VIDEO OR PHONE:
IF MATCHES FOUND AT 1 ADDRESS /
IF MATCHES FOUND AT MORE THAN ONE ADDRESS:

Question

Next, we have a few questions about your personal experiences. Do you personally know someone who moved to the U.S. from another country, or not?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

LIFEEXP_KNOWNIMMIG

Question

Have you gone hunting or fishing in the past year, or not?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

LIFEEXP_HUNT, PAPI POST Q106

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Have you used public transportation in the past year, or not?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-4. Error
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

LIFEEXP_PUBTRANS, PAPI POST Q107

Note: The following specifications were implemented exclusively in the computerized survey instrument and are not applicable to the paper questionnaire.

Question

Have you ever been bitten by a shark, or not?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Yes
2. No

Survey Question(s)

LIFEEXP_SHARK

Question

We would like to ask you about some things people think about today. We are faced with many problems in this country, none of which can be solved easily or inexpensively. For each of the following problems, please indicate whether you think we’re spending too much money on it, too little money, or about the right amount.

First: the space exploration program.

Are we spending too much, too little, or about the right amount on the space exploration program?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

GSSPOST_NATSPAC

Universe

IF R IS IN GSS SAMPLE:

Question

Are we spending too much, too little, or about the right amount on improving and protecting the environment?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

GSSPOST_NATENVIR

Universe

IF R IS IN GSS SAMPLE:

Question

Are we spending too much, too little, or about the right amount on improving and protecting the nation’s health?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

GSSPOST_NATHEAL

Universe

IF R IS IN GSS SAMPLE:

Question

Are we spending too much, too little, or about the right amount on solving the problems of the big cities?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

GSSPOST_NATCITY

Universe

IF R IS IN GSS SAMPLE:

Question

Are we spending too much, too little, or about the right amount on halting the rising crime rate?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

GSSPOST_NATCRIME

Universe

IF R IS IN GSS SAMPLE:

Question

Are we spending too much, too little, or about the right amount on dealing with drug addiction?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Too much
2. Too little
3. About the right amount

Survey Question(s)

GSSPOST_NATDRUG

Universe

IF R IS IN GSS SAMPLE:

Question

Taken all together, how would you say things are these days—would you say that you are very happy, pretty happy, or not too happy?

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Very happy
2. Pretty happy
3. Not too happy

Survey Question(s)

GSSPOST_HAPPY

Universe

IF R IS IN GSS SAMPLE:

Question

Some people say they have experiences of being personally moved, touched, or inspired, while others say they do not have these experiences at all. How often, if at all, do you experience each of the following: At least once a day, almost every day, once or twice a week, once or twice a month, a few times per year, once a year or less, or never?

Felt particularly connected to the world around you

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. At least once a day
2. Almost every day
3. Once or twice a week
4. Once or twice a month
5. A few times a year
6. Once a year or less
7. Never

Survey Question(s)

GSSPOST_SPRTCONNCT

Universe

IF R IS IN GSS SAMPLE:

Question

Some people say they have experiences of being personally moved, touched, or inspired, while others say they do not have these experiences at all. How often, if at all, do you experience the following: At least once a day, almost every day, once or twice a week, once or twice a month, a few times per year, once a year or less, or never?

Felt a sense of a larger meaning or purpose in life

Value Labels

Survey Question(s)

GSSPOST_SPRTLRGR

Universe

IF R IS IN GSS SAMPLE:

Question

We are going to name some institutions in this country. As far as the people running these institutions are concerned, would you say that you have a great deal of confidence, only some confidence, or hardly any confidence at all in them?

U.S. Supreme Court

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. Only some
3. Hardly any

Survey Question(s)

GSSPOST_CONJUDGE

Universe

IF R IS IN GSS SAMPLE:

Question

As far as the people running these institutions are concerned, would you say that you have a great deal of confidence, only some confidence, or hardly any confidence at all in them?

Military

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. Only some
3. Hardly any

Survey Question(s)

GSSPOST_CONARMY

Universe

IF R IS IN GSS SAMPLE:

Question

As far as the people running these institutions are concerned, would you say that you have a great deal of confidence, only some confidence, or hardly any confidence at all in them?

Press

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. Only some
3. Hardly any

Survey Question(s)

GSSPOST_CONPRESS

Universe

IF R IS IN GSS SAMPLE:

Question

As far as the people running these institutions are concerned, would you say that you have a great deal of confidence, only some confidence, or hardly any confidence at all in them?

Scientific Community

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. A great deal
2. Only some
3. Hardly any

Survey Question(s)

GSSPOST_CONSCI

Universe

IF R IS IN GSS SAMPLE:

Question

People may encounter different mixes of political views in conversation. How about you? When you have political conversations with family, friends, neighbors and coworkers are the views you hear…

Value Labels

-9. Refused
-7. Insufficient partial, interview deleted
-6. No post interview
-5. Sufficient partial, breakoff
-1. Inapplicable
1. Almost all liberal views
2. Mostly liberal but some conservative views
3. About an equal mix
4. Mostly conservative but some liberal views
5. Almost all conservative views
6. I don’t have conversations about politics

Survey Question(s)

GSSPOST_NETWORKPOST

Universe

IF R IS IN GSS SAMPLE:

Question

Others present at time of interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_OTHPRESPO

Universe

IF MODE IS FTF:

Question

Others present at time of interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_OTHPRESPO

Universe

IF MODE IS FTF:

Question

Others present at time of interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_OTHPRESPO

Universe

IF MODE IS FTF:

Question

Others present at time of interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_OTHPRESPO

Universe

IF MODE IS FTF:

Question

Others present at time of interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_OTHPRESPO

Universe

IF MODE IS FTF:

Question

Others present at time of interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_OTHPRESPO

Universe

IF MODE IS FTF:

Question

Others present at time of interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_OTHPRESPO

Universe

IF MODE IS FTF:

Question

Is R a man or a woman?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Male
2. Female

Survey Question(s)

IWROBSPO_GENDERPO

Universe

IF MODE IS FTF:

Question

What would you estimate R’s age to be?

Value Labels

-8. Don’t know
-1. Inapplicable
80. 80 years or older

Survey Question(s)

IWROBSPO_ESTAGE

Universe

IF MODE IS FTF:

Question

R’s cooperation was:

Value Labels

-8. Don’t know
-1. Inapplicable
1. Very good
2. Good
3. Fair
4. Poor
5. Very poor

Survey Question(s)

IWROBSPO_COOPPO

Universe

IF MODE IS FTF:

Question

R’s general level of information about politics and public affairs seemed:

Value Labels

-8. Don’t know
-1. Inapplicable
1. Very high
2. Fairly high
3. Average
4. Fairly low
5. Very low

Survey Question(s)

IWROBSPO_LEVINFPO

Universe

IF MODE IS FTF:

Question

R’s apparent intelligence:

Value Labels

-8. Don’t know
-1. Inapplicable
1. Very high
2. Fairly high
3. Average
4. Fairly low
5. Very low

Survey Question(s)

IWROBSPO_INTELLPO

Universe

IF MODE IS FTF:

Question

How suspicious did R seem to be about the study before the interview?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Not at all suspicious
2. Somewhat suspicious
3. Very suspicious

Survey Question(s)

IWROBSPO_SUSPICPO

Universe

IF MODE IS FTF:

Question

Overall, how great was R’s interest in the interview?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Very high
2. Fairly high
3. Average
4. Fairly low
5. Very low

Survey Question(s)

IWROBSPO_INTIWPO

Universe

IF MODE IS FTF:

SAMPLE VARIABLES

Question

How honest did R seem to be in his or her answers?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Completely honest
2. Usually honest
3. Often seemed to be dishonest

Survey Question(s)

IWROBSPO_HONESTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

ADMINISTRATIVE VARIABLES

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

R’s reaction to interview:

Value Labels

-1. Inapplicable
0. Not mentioned
1. Mentioned

Survey Question(s)

IWROBSPO_REACTPO

Universe

IF MODE IS FTF:

Question

Did you enter any of the CASI answers, or did the respondent enter all of the answers in CASI?

Value Labels

-8. Don’t know
-1. Inapplicable
1. Respondent entered all CASI answers
2. Interviewer entered at least one CASI answer

Survey Question(s)

IWROBSPO_CASIANSPO

Universe

IF MODE IS FTF:

Value Labels

1. Alabama  2. Alaska  4. Arizona
5. Arkansas  6. California  8. Colorado
9. Connecticut  10. Delaware
11. Washington DC
12. Florida  13. Georgia   15. Hawaii
16. Idaho   17. Illinois   18. Indiana
19. Iowa   20. Kansas   21. Kentucky
22. Louisiana   23. Maine   24. Maryland
25. Massachusetts   26. Michigan   27. Minnesota
28. Mississippi   29. Missouri   30. Montana
31. Nebraska   32. Nevada   33. New Hampshire
34. New Jersey   35. New Mexico   36. New York
37. North Carolina   38. North Dakota   39. Ohio
40. Oklahoma   41. Oregon   42. Pennsylvania
44. Rhode Island   45. South Carolina   46. South Dakota
47. Tennessee   48. Texas   49. Utah
50. Vermont   51. Virginia   53. Washington
54. West Virginia   55. Wisconsin   56. Wyoming

Value Labels

-3. RESTRICTED

Value Labels

-3. RESTRICTED

Value Labels

-3. RESTRICTED

Value Labels

-3. RESTRICTED

Value Labels

1. Northeast
2. Midwest
3. South
4. West

Value Labels

1. Eastern
2. Central
3. Mountain
4. Pacific
5. Alaska
6. Hawaii-Aleutian

SCREENER VARIABLES

Survey Question(s)

PAPI PRE Q47

Variable Note

For PAPI cases, survey completion dates were only collected for the pre-election survey; completion dates were not collected for the post-election survey. This pertains only to PAPI cases.

RANDOMIZATION VARIABLES

Value Labels

-2. Missing

Value Labels

-1. Inapplicable

Value Labels

-1. Inapplicable
0. Did not login with mobile phone
1. Logged in with mobile phone

Value Labels

-1. Inapplicable
0. Did not login with desktop computer
1. Logged in with mobile desktop compute

Value Labels

-1. Inapplicable
0. Did not login with tablet
1. Logged in with mobile tablet

Value Labels

-1. Inapplicable
0. Did not login with mobile phone
1. Logged in with mobile phone

Value Labels

-1. Inapplicable
0. Did not login with desktop computer
1. Logged in with desktop computer

Value Labels

-1. Inapplicable
0. Did not login with tablet
1. Logged in with tablet

Value Labels

-2. Data will be available in the 2024 ANES Methodology file

Value Labels

-2. Data will be available in the 2024 ANES Methodology file

Value Labels

-2. Data will be available in the 2024 ANES Methodology file

Value Labels

-1. Inapplicable
1. Forward order
2. Reverse order

Value Labels

-1. Inapplicable
1. Democrats / Republicans
2. Republicans / Democrats

Value Labels

-1. Inapplicable
1. Selected for GAYMARR
2. Selected for GAYMARR2

Value Labels

-1. Inapplicable
1. Harris / Trump
2. Trump / Harris

Value Labels

-1. Inapplicable
1. Democrats / Republicans
2. Republicans / Democrats

Value Labels

-1. Inapplicable
1. Israelis / Palestinians
2. Palestinians / Israelis

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. EMOTHOPE
1. EMOTAFRAID
2. EMOTRAGE
3. EMOTANGRY
4. EMOTHAPPY
5. EMOTWORRY
6. EMOTPROUD
7. EMOTIRRIT
8. EMOTNERV

Value Labels

-1. Inapplicable
0. THDPC
1. THRPC
2. THBIDEN

Value Labels

-1. Inapplicable
0. THDPC
1. THRPC
2. THBIDEN

Value Labels

-1. Inapplicable
0. THDPC
1. THRPC
2. THBIDEN

Value Labels

-1. Inapplicable
0. THRFK
1. THSHAPIRO
2. THWHITMER
3. THKELLY
4. THCOOPER
5. THDVPC
6. THRVPC

Value Labels

-1. Inapplicable
0. THRFK
1. THSHAPIRO
2. THWHITMER
3. THKELLY
4. THCOOPER
5. THDVPC
6. THRVPC

Value Labels

-1. Inapplicable
0. THRFK
1. THSHAPIRO
2. THWHITMER
3. THKELLY
4. THCOOPER
5. THDVPC
6. THRVPC

Value Labels

-1. Inapplicable
0. THRFK
1. THSHAPIRO
2. THWHITMER
3. THKELLY
4. THCOOPER
5. THDVPC
6. THRVPC

Value Labels

-1. Inapplicable
0. THRFK
1. THSHAPIRO
2. THWHITMER
3. THKELLY
4. THCOOPER
5. THDVPC
6. THRVPC

Value Labels

-1. Inapplicable
0. THRFK
1. THSHAPIRO
2. THWHITMER
3. THKELLY
4. THCOOPER
5. THDVPC
6. THRVPC

Value Labels

-1. Inapplicable
0. THRFK
1. THSHAPIRO
2. THWHITMER
3. THKELLY
4. THCOOPER
5. THDVPC
6. THRVPC

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
0. LEAD
1. CARE
2. KNOW
3. HONST
4. ENERG

Value Labels

-1. Inapplicable
0. LEAD
1. CARE
2. KNOW
3. HONST
4. ENERG

Value Labels

-1. Inapplicable
0. LEAD
1. CARE
2. KNOW
3. HONST
4. ENERG

Value Labels

-1. Inapplicable
0. LEAD
1. CARE
2. KNOW
3. HONST
4. ENERG

Value Labels

-1. Inapplicable
0. LEAD
1. CARE
2. KNOW
3. HONST
4. ENERG

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
1. Democrat, Republican
2. Republican, Democrat

Value Labels

-1. Inapplicable
0. FSSS
1. FSPUBS
2. FSBRDR
3. FSCRM
4. FSWELF
5. FSHIGH
6. FSPR
7. FSENV

Value Labels

Same as V244044

Value Labels

Same as V244044

Value Labels

Same as V244044

Value Labels

Same as V244044

Value Labels

Same as V244044

Value Labels

Same as V244044

Value Labels

Same as V244044

Value Labels

-1. Inapplicable
0. FELON
1. DOCS
2. SEXHAR

Value Labels

-1. Inapplicable
0. FELON
1. DOCS
2. SEXHAR

Value Labels

-1. Inapplicable
0. FELON
1. DOCS
2. SEXHAR

Value Labels

-1. Inapplicable
0. FBI (CBS)
1. Hannity (Fox)
2. Jesse Watters Primetime (Fox)
3. The Rachel Maddow Show (MSNBC)
4. The Last Word with Lawrence O’Donnell (MSNBC)
5. The Five (Fox)
6. The Ingraham Angle (Fox)
7. Gutfeld! (Fox)
8. The Lead with Jake Tapper (CNN)
9. Shark Tank (ABC)
10. Special Report with Bret Baier (Fox)
11. CBS Evening News with Norah O’Donnell
12. World News Tonight with David Muir (ABC)
13. Nightly News with Lester Holt (NBC)
14. Fareed Zakaria GPS (CNN)
15. NCIS (CBS)
16. The Daily Show with Jon Stewart
17. Anderson Cooper 360 (CNN)
18. Erin Burnett OutFront (CNN)
19. 60 Minutes (CBS)
20. 20/20 (ABC)
21. Dateline (NBC)
22. Face the Nation (CBS)
23. Meet the Press (NBC)
24. The Price is Right (CBS)
25. Good Morning America (ABC)
26. Today (NBC)
27. Outnumbered (Fox)
28. Deadline: White House (MSNBC)
29. All In with Chris Hayes (MSNBC)
30. The 11th Hour with Stephanie Ruhle (MSNBC)
31. PBS NewsHour
32. Saturday Night Live (NBC)

Variable Note

R’s that self-identified as Hispanic at V241499 received an extra set of Spanish language television programs in the response options; these were randomized along with the English language television programs. A full randomization sequence was created for both English only and English plus Spanish response options for all respondents. If V241499 = 1, the randomization for the English plus Spanish language television programs was utilized and is described in variables V244088 through V244136. If V241499 = 2, the randomization sequence for English only television programs was utilized and is described in variables V244055 through V244087.

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Same as V244055

Value Labels

Variable Note

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

Same as V244088

Value Labels

-1. Inapplicable
0. DONATE,SPENDLIM,ORG,DIRECT
1. DONATE,SPENDLIM,DIRECT,ORG
2. DONATE,ORG,DIRECT,SPENDLIM
3. DONATE,DIRECT,ORG,SPENDLIM
4. SPENDLIM,ORG,DIRECT,DONATE
5. SPENDLIM,DIRECT,ORG,DONATE
6. ORG,DIRECT,SPENDLIM,DONATE
7. DIRECT,ORG,SPENDLIM,DONATE

Value Labels

1. Democrat, Republican
2. Republican, Democrat

Value Labels

1. THPODPC, THPORPC
2. THPORPC, THPODPC

Value Labels

0. THPOSDC
1. THPOSRC
2. THPOSSDC
3. THPOSSRC
4. THPODVPC
5. THPORVPC
6. BIDEN

Value Labels

0. THPOSDC
1. THPOSRC
2. THPOSSDC
3. THPOSSRC
4. THPODVPC
5. THPORVPC
6. BIDEN

Value Labels

0. THPOSDC
1. THPOSRC
2. THPOSSDC
3. THPOSSRC
4. THPODVPC
5. THPORVPC
6. BIDEN

Value Labels

0. THPOSDC
1. THPOSRC
2. THPOSSDC
3. THPOSSRC
4. THPODVPC
5. THPORVPC
6. BIDEN

Value Labels

0. THPOSDC
1. THPOSRC
2. THPOSSDC
3. THPOSSRC
4. THPODVPC
5. THPORVPC
6. BIDEN

Value Labels

0. THPOSDC
1. THPOSRC
2. THPOSSDC
3. THPOSSRC
4. THPODVPC
5. THPORVPC
6. BIDEN

Value Labels

0. THPOSDC
1. THPOSRC
2. THPOSSDC
3. THPOSSRC
4. THPODVPC
5. THPORVPC
6. BIDEN

Value Labels

0. THGRFUND
1. THGRFEM
2. THGRLIB
3. THGRLAB
4. THGRBIGB
5. THGRCONS
6. THGRSCT
7. THGRGAY
8. THGRCONG
9. THGRMUSL
10. THGRXTIAN
11. THGRMAGA
12. JEWS
13. POLICE
14. TRANS
15. BLM

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

Same as V244210

Value Labels

0. NRA
1. FBI
2. RURAL
3. PLANPARENT

Value Labels

0. NRA
1. FBI
2. RURAL
3. PLANPARENT

Value Labels

0. NRA
1. FBI
2. RURAL
3. PLANPARENT

Value Labels

0. NRA
1. FBI
2. RURAL
3. PLANPARENT

Value Labels

0. ILLIMMIG
1. COST
2. CLIMCHNG
3. GUN
4. ABRT
5. CRIME
6. GAZAWAR
7. PUBSCHL
8. DEMOC
9. RACEINEQ

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

Same as V244230

Value Labels

0. OWNILLIMIG
1. OWNCOST
2. OWNCLIMCHNG
3. OWNABRT
4. OWNCRIME
5. OWNPUBSCHL

Value Labels

0. OWNILLIMIG
1. OWNCOST
2. OWNCLIMCHNG
3. OWNABRT
4. OWNCRIME
5. OWNPUBSCHL

Value Labels

0. OWNILLIMIG
1. OWNCOST
2. OWNCLIMCHNG
3. OWNABRT
4. OWNCRIME
5. OWNPUBSCHL

Value Labels

0. OWNILLIMIG
1. OWNCOST
2. OWNCLIMCHNG
3. OWNABRT
4. OWNCRIME
5. OWNPUBSCHL

Value Labels

0. OWNILLIMIG
1. OWNCOST
2. OWNCLIMCHNG
3. OWNABRT
4. OWNCRIME
5. OWNPUBSCHL

Value Labels

0. OWNILLIMIG
1. OWNCOST
2. OWNCLIMCHNG
3. OWNABRT
4. OWNCRIME
5. OWNPUBSCHL

Value Labels

1. GENDMASC, GENDFEM
2. GENDFEM, GENDMASC

Value Labels

0. CHINA
1. RUSSIA
2. MEXICO
3. IRAN
4. JAPAN
5. ISRAEL

Value Labels

0. CHINA
1. RUSSIA
2. MEXICO
3. IRAN
4. JAPAN
5. ISRAEL

Value Labels

0. CHINA
1. RUSSIA
2. MEXICO
3. IRAN
4. JAPAN
5. ISRAEL

Value Labels

0. CHINA
1. RUSSIA
2. MEXICO
3. IRAN
4. JAPAN
5. ISRAEL

Value Labels

0. CHINA
1. RUSSIA
2. MEXICO
3. IRAN
4. JAPAN
5. ISRAEL

Value Labels

0. CHINA
1. RUSSIA
2. MEXICO
3. IRAN
4. JAPAN
5. ISRAEL

Value Labels

0. PREFERDEM
1. COURTS
2. STRLEAD
3. REPWOMEN

Value Labels

0. PREFERDEM
1. COURTS
2. STRLEAD
3. REPWOMEN

Value Labels

0. PREFERDEM
1. COURTS
2. STRLEAD
3. REPWOMEN

Value Labels

0. PREFERDEM
1. COURTS
2. STRLEAD
3. REPWOMEN

Value Labels

0. INSTEADBUS
1. INSTEADEXP
2. INSTEADCIT

Value Labels

0. INSTEADBUS
1. INSTEADEXP
2. INSTEADCIT

Value Labels

0. INSTEADBUS
1. INSTEADEXP
2. INSTEADCIT

Value Labels

0. TRUSTCONG
1. TRUSTGOV
2. TRUSTJUD
3. TRUSTSCI
4. TRUSTPARTIES
5. TRUSTMEDIA
6. TRUSTSOCMEDIA

Value Labels

Same as V244260

Value Labels

Same as V244260

Value Labels

Same as V244260

Value Labels

Same as V244260

Value Labels

Same as V244260

Value Labels

Same as V244260

Value Labels

1. GENDPUBHLT, GENDECON
2. GENDECON, GENDPUBHLT

Value Labels

0. THGRASIAN
1. THGRHISP
2. THGRBLACK
3. THGRILLEG
4. THGRWHITE

Value Labels

0. THGRASIAN
1. THGRHISP
2. THGRBLACK
3. THGRILLEG
4. THGRWHITE

Value Labels

0. THGRASIAN
1. THGRHISP
2. THGRBLACK
3. THGRILLEG
4. THGRWHITE

Value Labels

0. THGRASIAN
1. THGRHISP
2. THGRBLACK
3. THGRILLEG
4. THGRWHITE

Value Labels

0. THGRASIAN
1. THGRHISP
2. THGRBLACK
3. THGRILLEG
4. THGRWHITE

Value Labels

0. HWKBLACK
1. HWKHISPREV
2. HWKASIAN

Value Labels

0. HWKBLACK
1. HWKHISPREV
2. HWKASIAN

INTERVIEWER DESCRIPTION VARIABLES

Value Labels

0. HWKBLACK
1. HWKHISPREV
2. HWKASIAN

Value Labels

0. VIOLBLACK
1. VIOLHISPREV
2. VIOLASIAN

Value Labels

0. VIOLBLACK
1. VIOLHISPREV
2. VIOLASIAN

Value Labels

0. VIOLBLACK
1. VIOLHISPREV
2. VIOLASIAN

Value Labels

0. DISCBLCK
1. DISCHISP
2. DISCASIAN
3. DISCWHT
4. DISCMUSL
5. DISCTIAN

Value Labels

0. DISCBLCK
1. DISCHISP
2. DISCASIAN
3. DISCWHT
4. DISCMUSL
5. DISCTIAN

Value Labels

0. DISCBLCK
1. DISCHISP
2. DISCASIAN
3. DISCWHT
4. DISCMUSL
5. DISCTIAN

Value Labels

0. DISCBLCK
1. DISCHISP
2. DISCASIAN
3. DISCWHT
4. DISCMUSL
5. DISCTIAN

Value Labels

0. DISCBLCK
1. DISCHISP
2. DISCASIAN
3. DISCWHT
4. DISCMUSL
5. DISCTIAN

Value Labels

0. DISCBLCK
1. DISCHISP
2. DISCASIAN
3. DISCWHT
4. DISCMUSL
5. DISCTIAN

Value Labels

0. DISCGAY
1. DISCWOM
2. DISCMEN
3. DISCTRANS

Value Labels

0. DISCGAY
1. DISCWOM
2. DISCMEN
3. DISCTRANS

Value Labels

0. DISCGAY
1. DISCWOM
2. DISCMEN
3. DISCTRANS

Value Labels

0. DISCGAY
1. DISCWOM
2. DISCMEN
3. DISCTRANS

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. $2500
2. $250,000

Value Labels

-7. Insufficient partial, interview deleted
-6. No post interview
-1. Inapplicable
1. $25
2. $250
3. $1000
4. $2500
5. $5000

Value Labels

-9. Refused
-1. Inapplicable

Value Labels

-9. Refused
-1. Inapplicable
1. Asian
2. Black
3. White
4. Other

Value Labels

-9. Refused
-1. Inapplicable
0. None
1. Hispanic
2. Other

Value Labels

-9. Refused
-1. Inapplicable
1. Male
2. Female

Value Labels

-9. Refused
-1. Inapplicable
4. Some college
5. College graduate
6. Master’s/PhD
9. Unknown

Value Labels

-1. Inapplicable
0. Not bilingual certified
1. Bilingual certified

Value Labels

-1. Inapplicable
0. Permission not given
1. Permission given

Value Labels

-1. Inapplicable
0. 0-4 years
1. 5-9 years
2. 10-14 years
3. 15+ years

Value Labels

-1. Inapplicable

Value Labels

-9. Refused
-1. Inapplicable

Value Labels

-9. Refused
-1. Inapplicable
1. Asian
2. Black
3. White
4. Other
5. Multiple mentions
9. Missing

Value Labels

-9. Refused
-3. Restricted
-1. Inapplicable
0. None
1. Hispanic
2. Other
9. Unknown

Value Labels

-9. Refused
-1. Inapplicable
0. Non-binary/other/unknown
1. Male
2. Female

Value Labels

-9. Refused
-1. Inapplicable
3. High school/GED
4. Some college
5. College graduate
6. Master’s/PhD
9. Unknown

Value Labels

-1. Inapplicable
0. Not bilingual certified
1. Bilingual certified

Value Labels

-1. Inapplicable
0. No
1. Yes

Value Labels

-1. Inapplicable
0. 0-4 years
1. 5-9 years
2. 10-14 years
3. 15 or more years

APPENDIX A: RELIGION CODES

These are numeric codes used in V241444x - PRE: SUMMARY: Full religion summary.

010. Protestant, NFS, other, unknown, inter-, or non-denominational
099. Christian, NFS, unknown, inter-, or non-denominational
100. 7th Day Adventist
101. Sabbatarian
109. Adventist (NFS)
110. Episcopalian; Anglican
120. American Baptist Association
121. American Baptist Churches USA (wrongly aka 'Northern Baptist')
122. Baptist Bible Fellowship
123. Baptist General Conference
124. Missionary Baptist; Baptist Missionary Association of America
125. Conservative Baptist Association of America
126. General Association of Regular Baptist Churches; GARB
127. National Association of Free Will Baptists; United Free Will Baptist Church
128. Primitive Baptist
129. National Baptist Convention in the USA
130. National Baptist Convention of America
131. National Primitive Baptist Convention of the USA
132. Progressive National Baptist Convention
133. National Baptist Convention NFS
134. Reformed Baptist (Calvinist)
135. Southern Baptist Convention
136. Full Gospel Baptist Church Fellowship
149. Baptist (NFS or other Baptist group not in codes 120-135)
150. United Church of Christ; UCC; Congregational; Congregationalist; Evangelical and Reformed Church
155. Congregational Christian
160. Church of the Brethren
161. Brethren (NFS)
162. Mennonite Church
163. Moravian Church
164. Old Order Amish
165. Quakers; Friends
166. Evangelical Covenant Church (not Anabaptist in tradition)
167. Evangelical Free Church, EFC, or EFCA (not Anabaptist in tradition)
168. Brethren in Christ
169. Apostolic Christian Church of America
170. Mennonite Brethren
171. Apostolic Christian Church Nazarene
180. Christian and Missionary Alliance; CMA; Alliance
181. Church of God (Anderson, IN)
182. Church of the Nazarene
183. Free Methodist Church
184. Salvation Army
 185. Wesleyan Church
186. Church of God of Findlay, OH
199. Pentecostal (NFS); Church of God (NFS); Holiness (NFS); not ascertained whether R Pentecostal or Charismatic (Holin
200. Plymouth Brethren
201. Independent Fundamental Churches of America; IFCA
219. Independent-Fundamentalist (NFS)
220. Evangelical Lutheran Church in America (formerly Lutheran Church in America and The American Lutheran Church); ELCA
221. Lutheran Church, Missouri Synod; LC-MS
222. Wisconsin Evangelical Lutheran Synod; WELS
224. Lutheran Free Church, Association of Free Lutheran Churches, AFLC
225. Church of the Lutheran Brethren
229. Lutheran (other or NFS)
230. United Methodist Church; Evangelical United Brethren
231. African Methodist Episcopal Church; AME
232. African Methodist Episcopal Zion Church
233. Christian Methodist Episcopal Church
234. Primitive Methodist
235. Congregational Methodist (fundamentalist)
240. Fire-Baptized Holiness
242. Assemblies of the Lord Jesus Christ; AJLC
243. Church of Our Lord Jesus Christ of the Apostolic Faith; COOLJC
244. Church of the Lord Jesus Christ of the Apostolic Faith; CLJC
245. Bible Way Church of Our Lord Jesus Christ
246. International Bible Way Church of Our Lord Jesus Christ
249. Methodist (other or NFS)
250. Assemblies of God; Assembly of God
251. Church of God (Cleveland, TN)
252. Church of God (Huntsville, AL)
253. International Church of the Four Square Gospel
254. Pentecostal Church of God
255. Pentecostal Holiness Church
256. United Pentecostal Church International
257. Church of God in Christ (incl. not ascertained whether 258)
258. Church of God in Christ International
260. Church of God of the Apostolic Faith
261. Church of God of Prophecy
262. Vineyard Fellowship
263. Open Bible Standard Churches
264. Full Gospel
267. Apostolic Pentecostal
270. Presbyterian Church in the U.S.A.
271. Cumberland Presbyterian Church
272. Presbyterian Church in America; PCA
275. Evangelical Presbyterian
276. Reformed Presbyterian
279. Presbyterian (other or NFS)
280. Christian Reformed Church (inaccurately known as 'Dutch Reformed')
281. Reformed Church in America
289. Reformed (other or NFS)
290. Christian Church; Disciples of Christ
291. Christian Churches and Churches of Christ
292. Churches of Christ; Church of Christ (NFS)
293. Christian Congregation
300. Christian Scientists
301. Mormons; Latter Day Saints; Community of Christ
303. Unitarian; Universalist
304. Jehovah's Witnesses
 305. Unity; Unity Church; Christ Church Unity
306. Fundamentalist Adventist; Worldwide Church of God; United Church of God
400. Roman Catholic
501. Orthodox
502. Conservative
503. Reform
524. Jewish, other, no preference, or NFS
600. Catholic and  Protestant
650. Messianic Judaism; Jews for Jesus
695. More than 1 major religion (e.g., Christian, Jewish, Muslim, etc.)
700. Greek Rite Catholic
701. Greek Orthodox
702. Russian Orthodox
703. Rumanian Orthodox
704. Serbian Orthodox
705. Syrian Orthodox
706. Armenian Orthodox
707. Georgian Orthodox
708. Ukrainian Orthodox
719. Eastern Orthodox (NFS or other specific Orthodox church)
720. Muslim; Islam
721. Buddhist
722. Hindu
723. Baha'i; Bahai
724. American Indian religions; Native American religions
725. New Age
726. Wicca; Wiccan
727. Pagan
730. Sikh
732. Konko Church
735. Spiritualists (not 'spiritual; must refer specifically to 'Spiritualism' or 'Spiritualists')
736. Religious Science; Science of Mind (not Scientology; not Christian Scientists); Centers for Spiritual Living
740. Other non-Christian /non-Jewish
750. Scientology
790. Religious /ethical cults
870. Other tradition not codeable to 010-790
879. R indicates having an affiliation but does not specify one
880. None
881. Agnostics
882. Atheists
888. DK whether considers self as part of a particular religion
889. RF to say if considers self as part of a particular religion

APPENDIX B: “MOST IMPORTANT PROBLEM” CODES

These are numeric codes used in V242165y1-y5, V242167y1-y5, V242169y1-y5, and V242171y1–y5.

1. Defense spending
2. Middle East
3. Iraq
4. War
5. Terrorism
6. Veterans
7. National defense (all other)
8. Foreign aid
9. Foreign Trade
10. Protection of US jobs
11. Serbia /Balkans
12. China
13. International affairs (all other)
14. Energy crisis
15. Energy prices
16. Energy (all other)
17. Environment
18. Natural Resources (all other)
19. Education and training
20. School funding
21. Education (all other)
22. AIDS
23. Medicare
24. Health (all other)
25. Welfare
26. Poverty
27. Employment
28. Housing
29. Social security
30. Income (all other)
31. Crime
32. Race relations
33. Illegal drugs
34. Police problems
35. Guns
36. Corporate Corruption
37. Justice (all other)
38. Budget
39. Size of government
40. Taxes
41. Immigration
42. Campaign finance
43. Political corruption
44. Ethics
45. Government power
46. Budget priorities
47. Partisan politics
48. Politicians
49. Government (all other)
50. The economy
51. Stock market
52. Economic inequality
53. Recession
54. Inflation
55. Economics (all other)
56. Agriculture
57. Science
58. Commerce
59. Transportation
60. Community development
61. Abortion
62. Child care
63. Overpopulation
64. Public morality
65. Domestic violence
66. Family
67. Young people
68. Sexual identity /LGBT+ issues
69. The media
75. Sexism /Gender issues
76. Afghanistan
77. Syria
78. Elections
79. Religion
80. Civility
81. Unity /division
82. Epidemic
700. Everything
750. All of them
800. Other problem
990. Not interpretable


Note: Code "-4" in the 2024 Time Series data is equivalent to code "997" (Other comment not matching any description) in the 2020 Time Series data.

Contents

ANES 2024 Time Series Study
Full Release

User Guide and Codebook

May 19, 2026

Acknowledgments

USER GUIDE

How to Cite the Study

Current Release

Sample Design

Sample Design

Respondent recruitment and retention

Pre-election study

Post-election study

Data Collection

Response Rates

Restricted Data Access

Data Analysis, Weights, and Variance Estimation

Weight variable selection

Sampling errors and significance testing

A note on subpopulation analysis or analysis with missing data

A note on weights and modes

Reporting weighted sample sizes

Weighting methods

Orientation to the Data and Documentation

Dataset

Questionnaire

User Guide and Codebook

CODEBOOK: VARIABLES

GENERAL NON‐SURVEY VARIABLES

WEIGHTING VARIABLES

PRE‐ ELECTION SURVEY VARIABLES

POST‐ELECTION SURVEY VARIABLES

SAMPLE VARIABLES

ADMINISTRATIVE VARIABLES

SCREENER VARIABLES

RANDOMIZATION VARIABLES

INTERVIEWER DESCRIPTION VARIABLES

APPENDIX A: RELIGION CODES

APPENDIX B: “MOST IMPORTANT PROBLEM” CODES

Contents

ANES 2024 Time Series StudyFull ReleaseUser Guide and Codebook

May 19, 2026

Acknowledgments

USER GUIDE

How to Cite the Study

Current Release

Sample Design

Sample Design

Respondent recruitment and retention

Pre-election study

Post-election study

Data Collection

Response Rates

Restricted Data Access

Data Analysis, Weights, and Variance Estimation

Weight variable selection

Sampling errors and significance testing

A note on subpopulation analysis or analysis with missing data

A note on weights and modes

Reporting weighted sample sizes

Weighting methods

Orientation to the Data and Documentation

Dataset

Questionnaire

User Guide and Codebook

CODEBOOK: VARIABLES

GENERAL NON‐SURVEY VARIABLES

WEIGHTING VARIABLES

PRE‐ ELECTION SURVEY VARIABLES

POST‐ELECTION SURVEY VARIABLES

SAMPLE VARIABLES

ADMINISTRATIVE VARIABLES

SCREENER VARIABLES

RANDOMIZATION VARIABLES

INTERVIEWER DESCRIPTION VARIABLES

APPENDIX A: RELIGION CODES

APPENDIX B: “MOST IMPORTANT PROBLEM” CODES

ANES 2024 Time Series Study
Full Release

User Guide and Codebook