American National Election Studies Research Articles

The Curious Case of Black “Conservatives”: Assessing the Validity of the Liberal-Conservative Scale among Black Americans

Abstract Many Black Americans identify as conservative on surveys, despite their allegiance to the Democratic Party. Prominent theoretical accounts claim this mismatch results from identity-based considerations. I revisit this long-standing puzzle and offer an alternative explanation with broad implications for studying political attitudes and behavior across the social sciences. Leveraging data from the American National Election Studies, I demonstrate that the terms “liberal” and “conservative” are unfamiliar to many Black Americans, compromising the usefulness and validity of the liberal-conservative scale for Black respondents. Respondents unfamiliar with these terms misapply them and choose ideological labels that fail to align with their partisan preferences. Consequently, scholars and political actors make incorrect and imprecise inferences about the contours of Black politics. Findings also raise new concerns about the generalizability of claims that rely on ideological self-identification measures, including popular claims about mass polarization and partisan-ideological sorting among the American public. Critically, this work suggests a need for caution when using concepts that vary in their meaningfulness across social groups.

Political rule (vs. opposition) predicts whether ideological prejudice is stronger in U.S. conservatives or progressives.

People see societal groups as less moral, warm, and likable if their ideology is more dissimilar to the ideology of the self (i.e., ideological prejudice). We contribute to the debate on whether ideological prejudice in the United States is stronger in conservatives, progressives, or neither. Investigating the American National Election Studies, we found that between 1972 and 2021, ideological prejudice was stronger in conservatives. However, investigating studies conducted to develop the agency-beliefs-communion model, we found that between 2016 and 2021, ideological prejudice was stronger in progressives. We report various analyses of both research programs and two new studies that rule out several explanations for this contradiction. Additional analytic and experimental evidence suggests that political rule (vs. opposition) may explain the robust heterogeneity in asymmetric ideological prejudice. Ideological prejudice shifted toward being stronger in conservatives when the United States was governed by Democrats and toward being stronger in progressives when the United States was governed by Republicans. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Racial Stereotypes, Racial Threat, and Support for Felon Disenfranchisement Among White Americans

Applying racial stereotypes and the racial threat framework to felon disenfranchisement support, this study argues white Americans who think Black Americans are more violent will be more supportive of felon disenfranchisement, and that this effect will be largest for white Republicans and white Americans who put greater importance in their racial identity. Analyses of the 2020 American National Election Study finds white Americans who think Black (white) Americans are more violent are more (less) supportive of felon disenfranchisement, with suggestive evidence these effects are more pronounced for white Republicans and white Americans holding greater racial importance. At the same time, the effects of violence stereotypes are consistently substantively small, amounting to less than one half of one level change in disenfranchisement support on a seven-point scale. These effect sizes are on par with partisanship, slightly smaller than other racial attitudes and crime spending preferences, and far outpaced by ideology. Overall, these results suggest racial stereotypes may factor into support for felon disenfranchisement, but these stereotypes are not a driving factor of such support.

Divergent views of party positions: How ideology and own issue position shape party perception through convergence and divergence processes

The current research explores how respondents’ ideology influences their perception of political parties’ stances on various issues. Additionally, we examine how three distinct indicators of ideological strength—congruence between ideology and party affiliation, level of education, and engagement in political activities—affect these perceptions. Our empirical analyses rely on data from the 1968–2012 Cumulative American National Election Study dataset, which captures respondents’ views on the stances of US political parties regarding ten key issues. We find that, after controlling for respondents’ own issue positions, (i) perceptions of the positions held by the opponent party are strongly influenced by respondents’ ideologies, and (ii) this influence is more pronounced among individuals with stronger ideological convictions, as indicated by the three aforementioned indicators. Conversely, when examining perceptions of one’s favored party, ideology demonstrates a weak and inconsistent effect across the three markers of ideological strength. We discuss theoretical frameworks that may elucidate these findings, their implications for understanding political polarization, and we acknowledge limitations related to the dataset’s characteristics.

Multiraciality and racialized politics in the United States

ABSTRACT In the United States, political ideology and political party affiliation provide important indicators of multiracial individuals’ place in the historic racial order. I ask the following research question: Do multiracials lean White or non-White in their political ideologies and political party affiliations? I argue that an individual’s racial identity shapes their political alignments, and multiracials’ alignments reveal how they affect racialized politics. I reference classic assimilation, minority trumping, and selection as theoretical frameworks that may indicate how multiracials are positioned in the contemporary racial order. Using the American National Election Study Time Series Studies (ANES 2008, 2012, 2016), I conduct a quantitative analysis (i.e. OLS regression models and multinomial logit models) and examine the relationship between respondents’ multiracial self-identification and political ideology and political party affiliation. Multiracials, who identify as White and non–White, experience an in-between effect, compared to their monoracial counterparts.

Landscape of Distrust: Political Trust Across America’s Urban-Rural Divide

Do rural Americans trust the government less than non-rural Americans? In an era of declining trust in government and mounting geographic polarization, this research examines the relationship between geography, identity, and attitudes of political trust in the United States. Using national survey data from the 2016 and 2020 American National Election Studies time series surveys, this quantitative analysis tests hypotheses that rurality in the context of place and place-based identity is associated with lower trust in the federal government. Overall, the results show that both living in and identifying with more rural areas corresponds with decreased government trust, regardless of the political party of the incumbent president. These findings contribute to the understanding of America’s urban-rural political divide and suggest significant implications for both partisan leaders and policymakers.

Populist Attitudes, Conspiracy Beliefs and the Justification of Political Violence at the US 2020 Elections

The months around the US 2020 presidential election were characterized by polarization, populism, conspiracy theories, and violent acts, far exceeding usual out-party animosity in western democracies. Using an original two-wave panel survey fielded before the election in November 2020 (n = 3111) and after the inauguration in January 2021 (n = 3384), supported with data from the American National Election Study (ANES, n = 3080), we investigate the dynamics of political violence justification and its connection with populist attitudes and conspiracy beliefs. While we find that conspiracy beliefs are associated with higher justification of violence, the relationship with populist attitudes is mixed, and mostly depends on whether people believe in conspiracy theories or not—with populist attitudes being associated with greater political violence justification among those who believe conspiracy theories, while having no or even a negative correlation among those who do not. Finally, results from fixed-effects models provide some evidence for a temporal interpretation of the relationships, indicating that an increase in conspiracy beliefs is strongly and consistently associated with an increased willingness to justify violence.

Voting in the Mall: Ideology, Grievance, and Political Consumerism

In this paper we consider how political ideology, attitudes toward historically-marginalized groups, and identification with grievance groups shape Americans’ self-reported participation in political consumerism (i.e., political boycotts and buycotts). Using data from the 2016 and 2020 American National Election Studies (ANES) surveys, we find that ideological intensity has an asymmetrical effect on boycott behavior in 2016, with strong liberals considerably more likely to engage in boycott behavior than strong conservatives. In 2020 the effect of ideological intensity shifts upward dramatically for conservatives, with both liberals and conservatives likely to engage in boycott behavior. We also find mixed results for the effects of attitudes toward and identification with historically-marginalized groups, though we do find that general political participation (and related variables) are strongly related to boycott activity. We discuss the implications of our findings, particularly as they relate to the effects of ideological intensity for liberals and conservatives.

Distrusting the Process: Electoral Trust, Operational Ideology, and Nonvoting Political Participation in the 2020 American Electorate.

This article explores the relationships between electoral trust, operational ideology, and nonvoting political participation (NVP) during the 2020 US presidential election cycle. We hypothesize that: (1) more liberal operational ideology is associated with more NVP, (2) less electoral trust is associated with more NVP, and (3) operational ideology moderates the negative relationship between electoral trust and NVP. Using data from the 2020 American National Election Study (N = 8,280), our contribution is threefold: We first add to previous research that indicated liberals engage in more NVP than conservatives. We then provide some of the first evidence to suggest that electoral trust-in this case, trust prior to the 2020 election-is negatively associated with NVP. Results further indicate that the negative relationship between electoral trust and NVP is strongest among those with conservative operational ideology, such that the more trust those with conservative operational ideology have in the election, the less they engage in NVP. Given that electoral trust is crucial for a well-functioning democracy, the implication is that elites with a strategic incentive to express contempt for the election process can have direct and downstream consequences on political participation.

Racial resentment, sexism, and evaluations of Kamala Harris in the 2020 U.S. presidential election

AbstractObjectiveThis article examines the effect of racial attitudes and sexism on evaluations of Kamala Harris. It also compares the effect of these variables on evaluations of other Democratic politicians: Joe Biden, Barack Obama, and Hillary Clinton.MethodsData are taken from the 2020 American National Election Studies, using feeling thermometers for Harris, Biden, and Obama, and from the 2016 American National Election Studies for Clinton. Our primary independent variables are racial resentment and three measures of sexism: modern, hostile, and traditional sexism.ResultsRacial resentment, modern sexism, and traditional sexism exerted an effect on evaluations of Kamala Harris above and beyond other explanatory variables, including party identification and ideology. However, these effects did not differ considerably from those found for Biden, Obama, and Clinton.ConclusionsRacial resentment and sexism appear to be related to evaluations of any Democratic presidential or vice presidential nominee, reflecting how they have become salient in defining party identities. We speculate, however, that their effects might be even more visible for black women at the top of a presidential ticket, and provide major headwinds into which Kamala Harris may have to run when contemplating any future presidential candidacy of her own.

Leveraging multiple digital footprint datasets to predict racial, sex-based, and sexual-orientation bias across US states

Introduction & BackgroundRacial, gender, and sexual-orientation biases are pervasive throughout society. Importantly, modern digitally oriented datasets can elucidate important societal variables and potential solutions. One contemporary theory that attempts to explain these biases is parasite-stress: an evolutionary psychology hypothesis suggesting that increased infectious diseases rates increase out-group biases. We present preliminary findings that suggest that disease rates are a meaningful geospatial predictor of multiple biases. Objectives & ApproachWe explored biases using geospatial analyses throughout multiple datasets based on US participants: Project Implicit, American National Election Studies (ANES), Google Trends, and Twitter/X. We included state-based variables to compare between states and assess the most important environmental-level predictors of biases. We built generalised linear and linear mixed-effect models and general linear models. Within Project implicit (n > 3,000,000) and ANES datasets (n > 30,000), we assessed racial and sexual-orientation biases via explicit and implicit measures. For Google Trends and Twitter/X datasets, we assessed racial and sex-based biases via search and tweet-per-state scores. To analyse the biases, we included environmental-level variables, e.g., infectious disease rates (developed by Thornhill and Fincher in 2014), and individual-level variables, e.g., political orientation. Relevance to Digital FootprintsThese preliminary findings analyse everyday people’s online behaviour including volunteered surveys, searches and posts. We attempt to address the pressing societal issue of bias by leveraging modern datasets. Our primary goal is to aid policy makers by recommending cost-effective solutions that can improve several factors of the population’s quality of life. ResultsWe find that the most consistently significant predictor of racial bias is infectious disease rates. When leveraging Google Trends data including anti-women terminology, infectious disease rates and population density are consistent predictors of bias. Finally, we find preliminary results suggesting that increased levels of infectious diseases increases homophobic bias. Conclusions & ImplicationsOverall, we find that as infectious disease rates increase in a state, the level of racial and sexist bias significantly increases. Consistent with parasite-stress theory, we argue that focusing on reducing infectious disease rates in an area can have a plethora of benefits including improving physical and mental health and reducing biases that damage society.

Increasing Voter Participation Through Health Care–Based Voter Registration

Young people and historically marginalized racial and ethnic groups are poorly represented in the democratic process. Addressing voting inequities can make policy more responsive to the needs of these communities. To assess whether leveraging health care settings as venues for voter registration and mobilization is useful, particularly for historically underrepresented populations in elections. In 2020, nonpartisan nonprofit Vot-ER partnered with health care professionals and institutions to register people to vote. This cross-sectional study analyzed the demographics and voting behavior of people mobilized to register to vote in health care settings, including hospitals, community health centers, and medical schools across the US. The age and racial and ethnic identity data of individuals engaged through Vot-ER were compared to 2 national surveys of US adults, including the 2020 Cooperative Election Study (CES) and the 2020 American National Election Study (ANES). Health care-based voter registration. The main outcomes were age composition, racial and ethnic composition, and voting history. Of the 12 441 voters contacted in health care settings, 41.9% were aged 18 to 29 years, 15.9% were identified as African American, 9.6% as Asian, 12.7% as Hispanic, and 60.4% as White. This distribution was significantly more diverse than the racial and ethnic distribution of the ANES (N = 5447) and CES (N = 39 014) samples, of which 72.5% and 71.19% self-identified as White, respectively. Voter turnout among health care-based contacts increased from 61.0% in 2016 to 79.8% in 2020, a turnout gain (18.8-percentage point gain) that was 7.7 percentage points higher than that of the ANES sample (11.1-percentage point gain). Demographically, the age distribution of voters contacted in health care settings was significantly different from the ANES and CES samples, with approximately double the proportion of young voters aged 18 to 29 years. This cross-sectional study suggests that health care-based voter mobilization reaches a distinctly younger and more racially and ethnically diverse population relative to those who reported contact from political campaigns. This analysis of the largest health care-based voter mobilization effort points to the unique impact that medical professionals may have on voter registration and turnout in the 2024 US elections. In the long term, health equity initiatives should prioritize expanding voting access to address the upstream determinants of health in historically marginalized communities.

Synthetic Replacements for Human Survey Data? The Perils of Large Language Models

Abstract Large language models (LLMs) offer new research possibilities for social scientists, but their potential as “synthetic data” is still largely unknown. In this paper, we investigate how accurately the popular LLM ChatGPT can recover public opinion, prompting the LLM to adopt different “personas” and then provide feeling thermometer scores for 11 sociopolitical groups. The average scores generated by ChatGPT correspond closely to the averages in our baseline survey, the 2016–2020 American National Election Study (ANES). Nevertheless, sampling by ChatGPT is not reliable for statistical inference: there is less variation in responses than in the real surveys, and regression coefficients often differ significantly from equivalent estimates obtained using ANES data. We also document how the distribution of synthetic responses varies with minor changes in prompt wording, and we show how the same prompt yields significantly different results over a 3-month period. Altogether, our findings raise serious concerns about the quality, reliability, and reproducibility of synthetic survey data generated by LLMs.

Younger Americans are less politically polarized than older Americans about climate policies (but not about other policy domains).

Political polarization of Americans' support for climate policies often impedes the adoption of new, urgently needed climate solutions. However, recent polls suggest that younger conservatives favor adopting pro-climate policies to a greater degree than older conservatives, resulting in less political polarization among younger Americans relative to older Americans. To better understand these patterns, we analyzed Americans' support for various climate policies from 1982-2020, across 16 waves of historical, nationally representative survey data from the American National Election Studies (total N = 29,467). Regression models consistently show that, since 2012, younger Americans have been less politically polarized than older Americans on support for climate policies. Before 2012 and on non-climate policy topics, we did not find consistent statistical evidence for political polarization varying with age. These findings can inform policy debates about climate change and offer hope to environmentalists and policymakers who seek to build broad consensus for climate action at the policy level.

The personality of a personality cult? Personality characteristics of Donald Trump's most loyal supporters

AbstractThe unusually loyal supporters of Donald Trump are often described as a cult. How can we understand this extreme phenomenon in U.S. politics? We develop theoretical expectations and use the Big Five personality dimensions to investigate whether Trump's most loyal supporters share personality characteristics that might make them inclined to cult‐like support. We find that (1) Trump's supporters share high levels of Conscientiousness; (2) this is substantively and statistically distinguishable from the commonly identified association between Conscientiousness and Conservatism; and (3) the association is highly robust to a range of sensitivity tests. Our main findings are robust across two surveys. Study 1 is an online survey conducted in 2021 designed specifically for this project. Study 2 is the 2016 American National Election Study (ANES).

Trump Voters' social position in U.S. Society: Uniqueness and radical‐right support

Trump Voters' social position in U.S. Society: Uniqueness and radical‐right support

Institutional knowledge and perceived rural representation

Place-based identities could potentially shape how the public evaluates political information, especially when cleavages between rural and non-rural become more central to politics. Rural voters may particularly respond distinctly to knowledge about the United States political system, which through several political institutions, notably the federal Senate, gives rural areas a share of votes exceeding their share of the population. Observational survey responses from the 2020 American National Election Study show that although most respondents feel that government institutions give less political influence to rural areas, knowledge about American politics reduces that feeling. The relationship between this knowledge and beliefs about rural political influence, however, occurs only in those with suburban and, especially, urban identities; rural and small-town identifiers seemingly shrug off their knowledge in assessing rural political influence.

Validating the “Genuine Pipeline” to Limit Social Desirability Bias in Survey Estimates of Voter Turnout

Abstract It is well documented that survey overreporting of voter turnout due to social desirability bias threatens inference about political behavior. This paper reports four studies that contained question wording experiments to test questions designed to minimize that bias using a “pipeline” approach. The “pipeline” informs survey participants that researchers can perform vote validation to verify turnout self-reports. This approach reduced self-reported turnout by 5.7 points in the 2020 American National Election Study, which represents a majority of the estimated overreporting bias. It reduced reported turnout by 4 points in two nonprobability samples. No effect was found in a third nonprobability study with Amazon Mechanical Turk workers. Validated vote data also confirm that the pipeline approach reduced overreporting. We tested heterogeneous effects for sophistication and several other variables, but results were inconclusive. The pipeline approach reduces overreporting of voter turnout and produces more accurate estimates of voters’ characteristics.

Open Questions Self-Administered on the Web versus Interviewer-Administered in Person: The 2016 American National Election Study Mode Comparison

Abstract Relatively little is known about the performance of open questions in self-administered questionnaires compared to interviewer-administered ones. We examined this issue using the responses to the 2016 American National Election Study’s Web self-administered questionnaires and face-to-face computer-assisted personal interviews (CAPI) from independently drawn samples that asked three sets of open questions: most important problem(s) facing the country; candidate for and against reasons; and political party likes and dislikes. Although Web respondents gave shorter answers with fewer codeable ideas than face-to-face respondents, the two modes produced similar distributions of substantive answers. Despite our expectation that open answers to interviewers would be more civil than those expressed on the Web, there was no difference in civility between the modes. However, the construct validity of the four candidate for and against items (predicting vote choice of Clinton vs. Trump) was higher on the Web than in the interviewer-administered CAPI. These findings call into question the conventional wisdom that open questions are not well suited for self-administration and suggest that researchers should consider more frequent use of open questions in Web surveys.

Altruistic concern: how racial ideologies explain racial differences in concerns for Black victims of crime and the police

We explore how concerned Americans are about the risk of violence faced by Black Americans. Using a 2022 American National Election Studies (ANES) survey, we compare concern for Black Americans as the victims of crime versus the police. We find White Americans to be the least concerned about both kinds of victimization, Black Americans the most concerned, and Latinx Americans in between. Interestingly, White Americans expressed significantly less concern about Black Americans being victimized by the police than by civilians. People’s racial ideologies play the largest role in explaining the average differences in concern between people with different racial identifications.