Perceived vulnerability to infectious disease and perceived harmfulness are as predictive of citizen response to COVID-19 as partisanship.

Partisans have biased perceptions of objective conditions. At first glance, the COVID-19 pandemic would appear to be an example of this phenomenon. Noting that most citizens have consistently agreed about the pandemic, I argue that we have overlooked pre-political factors that are as influential as partisanship in shaping citizens' responses to the pandemic. I identify one such construct in perceived vulnerability to infectious disease (PVD). In one cross-sectional study and one panel study, I find that the influence of PVD on citizens' perceptions of COVID-19 equals that of partisanship. I also find that PVD can moderate the influence of partisanship on perceptions of harmfulness, nearly erasing the impact of being a Republican on perceiving COVID-19 as a threat. When led by PVD as well as partisanship to accurately perceive harm, citizens, including Republicans, attribute more responsibility to former president Donald Trump for his failed handling of the crisis.

Is fair representation good for children? effects of electoral partisan bias in state legislatures on policies affecting children's health and well-being.

Increasing evidence suggests that state policies impact constituents' health, but political determinants of health and health inequities remain understudied. Using state and year fixed-effects models, we determined the extent to which changes in electoral partisan bias in lower chambers of U.S. state legislatures (i.e., discrepancy between statewide vote share and seat share) were followed by changes in five state policies affecting children and families (1980-2019) and a composite of safety net programs (1999-2018). We examined effects on each policy and whether the effect was modified when bias was accompanied by unified party control. Next, we determined whether the effect differed depending on which party it favored. Less bias resulted only in higher AFDC/TANF benefits. Both pro-Democratic and pro-Republican bias was followed by decreased AFDC/TANF benefits and increased Medicaid benefits. AFDC/TANF recipients, unemployment benefits, minimum wage, and pre-K-12 education spending increased following pro-Democratic bias and decreased following pro-Republican bias. Estimated effects on the composite measure of safety net policies were all close to null. Some effects were modulated by unified party control. Results demonstrate that increasing fairness in elections is not a panacea by itself for increasing generosity of programs affecting children's well-being. Indeed, bias can be somewhat beneficial for the expansiveness of some policies. Furthermore, with the exception of unemployment benefits and AFDC/TANF recipients, Democrats have not been using the additional power that comes with electoral bias to spend more on major programs that benefit children. Finally, after decades in which electoral bias was in Democrats' favor, bias has started to shift toward Republicans in the last decade. This trend forecasts more cuts in almost all the policies in this study, especially education and AFDC/TANF recipients. There is a need for more research and advocacy emphasis on the political determinants of social determinants of health, especially at the state level.

Motivated reasoning: Election integrity beliefs, outcome acceptance, and polarization before, during, and after the 2020 U.S. Presidential Election.

The 2020 U.S. Presidential Election required voters to not only form opinions of leading candidates, Donald Trump and Joe Biden, but also to make judgments about the integrity of the election itself and what-if anything-to do about it. However, partisan motivated reasoning theory (Leeper and Slothuus, Political Psychology, 35(Suppl 1): 129-156; Lodge and Taber, The rationalizing voter, Cambridge University Press, 2013) suggests judgments are often strongly influenced toward affectively desirable conclusions. Before, during, and after election projections were announced, partisan supporters of Trump and Biden rated: judgments about voter fraud and foreign interference, their acceptance of the results, and their support for recourse against the outcome (e.g., legal challenges, legislative overhauls, violence). Before the election, partisans were mildly concerned about election integrity but willing to accept the outcome without recourse. However, during vote counting, and especially after Biden was projected to be the winner, partisans dramatically changed their judgments in opposite directions, consistent with the affectively desirable conclusions relevant to each group. Biden supporters affirmed the election's integrity and accepted the results whereas Trump supporters disputed the integrity, rejected the results, and began to support recourse against the outcome. Data are consistent with partisan motivated reasoning. Discussion highlights the practical implications. Supplementary Information: The online version contains supplementary material available at 10.1007/s11031-022-09983-w.

Computational underpinnings of partisan information processing biases and associations with depth of cognitive reasoning.

Despite unprecedented access to information, partisans increasingly disagree about basic facts that are backed by data, posing a serious threat to a democracy that relies on finding common ground based on objective truths. We examine the underpinnings of this phenomenon using drift diffusion modeling (DDM). Partisans (N = 148) completed a sequential sampling task where they evaluated the honesty of Democrat or Republican politicians during a debate based on fact-check scores. We found that partisans required less and weaker evidence to correctly categorize the ingroup as more honest, and were more accurate on trials when the ingroup candidate was more honest, compared to the outgroup. DDM revealed that such tendencies arise from both a prior preference for categorizing the ingroup as more honest (i.e., biased starting point) and more precise accumulation of information favoring the ingroup candidate compared to the outgroup (i.e., biased drift rate). Moreover, individual differences in cognitive reasoning moderated task performance for the most devoted partisans and maintained divergent associations with the DDM parameters. This suggests that partisans may reach biased conclusions via different pathways depending on their depth of cognitive reasoning. These findings provide key insights into the mechanisms driving partisan divides in polarized environments, and can inform interventions that reduce impasse and conflict.

Color War. Does Color Influence the Perception of Political Messages?

Several studies have shown that exposure to colors affects cognitive and affective processes. In this paper, we tried to find if colors affect the perception of political messages and activate partisan biases. We focus our study on the Spanish cultural environment. In a prestudy (n = 991), participants identified red as progressive, blue as conservative, and gray as neutral. In two subsequent experiments (n = 840; n = 938), we analyzed how these three colors influenced the interpretation of political messages and confronted them with issues ownership. The results show that the colors can activate partisan biases but do not have the same strength as issues ownership.

Response Decoupling and Partisans' Evaluations of Politicians' Transgressions.

There is growing interest in the study of expressive responding in public opinion surveys, with scholars seeking to determine whether partisan differences in response to survey items attest to genuine differences in perceptions or to insincere responses meant to signal in-party approval or out-party disapproval. This study focuses on partisan gaps in evaluations of the inappropriateness of politicians' transgressions and tests the effectiveness of a technique designed to reduce expressive responding. This "response decoupling" technique gives respondents the opportunity to separate their evaluations of a politician's performance from their evaluations of a transgression committed by the politician, thereby allowing partisans to both disapprove of the transgression and signal support for the politician. The technique was experimentally tested in a study in Israel (N = 906) and in two pre-registered studies in the US (total N = 3,172), as these studies presented respondents with a real-life transgression of an actual politician. Overall, the technique had a weak effect, as only in the Israeli study was the effect statistically significant. On the whole, these results suggest that while partisan gaps in evaluations of politicians' transgressions may reflect genuine perceptual differences, it may also be the case that allowing respondents to decouple their responses is not a sufficiently powerful method to reduce expressive responding. The paper concludes by discussing the implications and limitations of these findings. Supplementary information: The online version contains supplementary material available at 10.1007/s11109-022-09796-0.

Stepping Outside the Echo Chamber: Is Intellectual Humility Associated With Less Political Myside Bias?

In recent years, an upsurge of polarization has been a salient feature of political discourse in America. A small but growing body of research has examined the potential relevance of intellectual humility (IH) to political polarization. In the present investigation, we extend this work to political myside bias, testing the hypothesis that IH is associated with less bias in two community samples (N1 = 498; N2 = 477). In line with our expectations, measures of IH were negatively correlated with political myside bias across paradigms, political topics, and samples. These relations were robust to controlling for humility. We also examined ideological asymmetries in the relations between IH and political myside bias, finding that IH-bias relations were statistically equivalent in members of the political left and right. Notwithstanding important limitations and caveats, these data establish IH as one of a small handful psychological features known to predict less political myside bias.

A Signal Detection Approach to Understanding the Identification of Fake News.

Researchers across many disciplines seek to understand how misinformation spreads with a view toward limiting its impact. One important question in this research is how people determine whether a given piece of news is real or fake. In the current article, we discuss the value of signal detection theory (SDT) in disentangling two distinct aspects in the identification of fake news: (a) ability to accurately distinguish between real news and fake news and (b) response biases to judge news as real or fake regardless of news veracity. The value of SDT for understanding the determinants of fake-news beliefs is illustrated with reanalyses of existing data sets, providing more nuanced insights into how partisan bias, cognitive reflection, and prior exposure influence the identification of fake news. Implications of SDT for the use of source-related information in the identification of fake news, interventions to improve people's skills in detecting fake news, and the debunking of misinformation are discussed.

Partisan Bias in Message Selection: Media Gatekeeping of Party Press Releases.

Parties try to shape media coverage in ways that are favorable to them, but what determines whether media outlets pick up and report on party messages? Based on content analyses of 1,496 party press releases and 6,512 media reports from the 2013 Austrian parliamentary election campaign, we show that media coverage of individual party messages is influenced not just by news factors, but also by partisan bias. The media are therefore more likely to report on messages from parties their readers favor. Importantly, this effect is greater rather than weaker when these messages have high news value. These findings have important implications for understanding the media's role in elections and representative democracies in general.