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A Different Kind of Disadvantage: Candidate Race, Cognitive Complexity, and Voter Choice

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Abstract

Voters use heuristics to help them make decisions when they lack information about political choices. Candidate appearance operates as a powerful low-information cue. However, widely held stereotypes mean that reliance on such a heuristic can reduce support for candidates of color. We argue that racial prejudices are more likely to dominate decision making when electoral environments require voters to expend more cognitive resources—such as when they must choose multiple candidates at once. Using two experiments we find that black candidates receive less support from cognitively taxed voters than from voters who have the cognitive space to intentionally limit their prejudices when voting. We also reveal that this pattern is particularly evident among ideologically liberal voters. Respondents who profess politically liberal views support black candidates more often than white candidates when the cognitive task is simple but are less likely to do so when they are cognitively taxed.

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Notes

  1. In our conception, prejudice may either be implicit (and thus, unknown to the respondent), or explicit but suppressed for some other reason (e.g. social desirability or conflicting egalitarian attitudes). In either case, we expect cognitive complexity to increase the role of prejudice in decisions.

  2. Our own analysis of General Social Survey Data from 1998 to 2008 confirms that both white liberals and white Democrats hold such stereotypes and that the differences in their ratings of whites and African Americans on these dimensions are significantly different from zero. Results available from the authors.

  3. While implicit attitudes are automatic and unconscious, explicit attitudes are deliberate and intentional. Research shows that both implicit and explicit attitudes can affect vote choice and policy preferences (Mo 2015; Perez 2010; Payne et al. 2010; Galdi et al. 2008; Lodge and Taber 2000, 2005; Burdein et al. 2006), but studies show that explicit attitudes tend to dominate in studies of vote choice (Ditonto et al. 2013; Kalmoe and Piston 2013; Kinder and Ryan 2017). Our theory focuses on how explicit attitudes—such as prejudicial negative stereotypes of blacks and beliefs about black candidates’ ideology—influence voter behavior.

  4. Some egalitarians may be expressing what is known as social desirability bias—the belief that revealing one’s racism is inappropriate (Krumpal 2013), while others might feel firmly committed to egalitarian ideals or hold genuine racial sympathy toward non-whites (Devine and Monteith 1993; Tesler 2016).

  5. Political liberals may also have a greater commitment to diversity/racial equality than political conservatives. Such a commitment will produce an observationally equivalent outcome in which liberals are more likely to select black candidates than conservatives under low cognitive load.

  6. Some research (Oliver 2012; Anzia 2014; Berry 2009) suggests that because of the general low levels of interest in local politics, local electorates are often disproportionately comprised of knowledgeable, motivated residents like home owners and municipal employees. Thus, the level of knowledge among voters may interact with cognitive complexity to affect the extent to which voters use racial stereotypes when casting ballots in real elections. In the Online Appendix we take advantage of distinctions in voter knowledge across real election contexts to test this possibility. Our analyses in Fig. OA1. suggest that more cognitively complex elections (at large contests where voters must select multiple candidates versus district contests where they select only one) do yield fewer black officeholders particularly in elections that are more likely to have low-information voters (on-cycle elections with higher turnout versus off-cycle elections with lower turnout). These tests suggest support for our theory in real elections and indicate the effects of cognitive complexity in provoking use of racial stereotypes among voters should be more common among lower than higher information voters.

  7. Replication materials are available in the Political Behavior Dataverse at https://doi.org/10.7910/dvn/mnao24.

  8. In total, there were 46 survey questions in Experiment 1 and 41 questions in Experiment 2.

  9. This paper is focused particularly on testing the role of cognitive complexity in shaping voter behavior—a test not present in existing research on candidate race and vote choice. Our experiments are designed to mimic one type of electoral context—low information elections, in which voters may see images of candidates on campaign mailers, etc. but have little other information about the candidates. Studies in Ireland, where ballots for local office include photographs, find that voters rely heavily on photographs as shortcuts for decision-making in low information elections (Buckley et al. 2007). To evaluate the effects of candidate race and ethnicity, we sought to remove as many other cues from our experimental ballots as possible—for example, we chose to cue candidate race using images of individuals in professional dress rather than names which could potentially also signal socioeconomic status or other cues.

  10. We used a total of 80 pictures in our experiments. These include 40 pictures of governors and senators from prior studies (Olivola and Todorov 2010; Todorov et al. 2005) that were calculated to be within two competency score standard deviations from one another and an additional 40 pictures of state or local elected officials from Arizona, Florida, Georgia, Hawaii, North Carolina, and Texas gathered online. Using MTurk, a separate sample of 966 participants rated each photo on attractiveness, competency, and trustworthiness similar to Todorov et al. 2005. There is no significant difference between the two sets of pictures with regard to competency. Our photos were judged to be very slightly more attractive and trustworthy. Summary statistics on these measures are in the Online Appendix Table OA2.

  11. Regarding racial and ethnic identification, respondents correctly identified the race or ethnicity of black and white candidates 89% of the time and Asian candidates 74% of the time. Latino candidates were only identified as Latino 39% of the time. When respondents made mistakes, Black and Asian candidates were nearly always categorized as some other racial minority (they were only perceived as white 2.6% of the time). But, Latino candidates were generally perceived as white (47% of the time). As many Latinos racially identify as white, this may simply reflect the complexity of Latino identification in the broader population and in actual elections with Latino candidates. Regarding ideology, when estimating the ideology of our candidate photos on a 7-point scale, with higher values meaning more conservative, on average respondents rated black candidates at 3.168 (i.e. solidly liberal) and white candidates at 4.701 (i.e. moderate leaning toward conservative)—a highly significant, one standard deviation difference (see appendix Table OA3).

  12. Prior to the cognitive load manipulations, respondents completed a set of text-based voting tasks separate from the dependent variables in this analysis. These are discussed in (Crowder-Meyer et al. 2017) but do not test the cognitive difficulty mechanism and are not discussed here. After the text-based voting task, all respondents engaged in two simple cognitive processing tasks—completing an analogy and an anagram—prior to being randomly assigned to the eye blink manipulation.

  13. As this was an online, anonymous survey we had no way to check the accuracy of the eye blink totals. On average our eye blink counters reported 22 blinks while answering five questions.

  14. In cities where councilors are elected at-large, there are commonly twice as many candidates as seats available for election in at-large contests (Trounstine 2008).

  15. We have exactly ten photos for each of eight categories: white men, white women, black men, black women, Latino men, Latina women, Asian men, and Asian women.

  16. For details on the task and samples, see the Online Appendix.

  17. We present the results for black candidates relative to white candidates. Estimated effects for Asian and Latino candidates are discussed in footnotes and are available from the authors by request.

  18. No controls for respondent attributes are needed because candidate race was randomized across respondents. Including characteristics like age, gender, marital status, and income does not affect the conclusions and the coefficients on such variables are essentially zero.

  19. Hainmueller et al. (2014) define the AMCE as “the increase in the population probability that a profile would be chosen if the value of its lth component was changed from t0 to t1, averaged over all the possible values of the other components given the joint distribution of the profile attributes p(t)” (p. 11).

  20. Our results are more mixed for Asian and Latino candidates. In Experiment 2, Asian and Latino candidates were not significantly more or less likely to be selected than whites in at-large versus district elections. In Experiment 1, Asian candidates even appear to benefit from the imposition of a higher cognitive load. Our theory predicts that voter behavior under heavy cognitive load is driven by racial stereotypes, thus these results are consistent with the presence of more mixed positive and negative stereotypes about Asians and Latinos in the US (see e.g. Kao 1995). Additionally, our findings for Asian candidates may indicate that positive stereotypes about Asian-Americans’ work ethic and intellect lead voters to prefer Asian candidates when stereotypes play a larger role in their decision-making (Kinder and Kam 2010).

  21. Respondents were asked their ideology on a 7-point scale. Liberals are those who said they are extremely liberal, liberal, or slightly liberal, while conservatives are extremely conservative, conservative, or slightly conservative. Respondents who insisted on choosing moderate even after a follow-up question prompting them to choose an ideological position or who said that they haven’t thought much about it are excluded from the following analysis.

  22. One alternative explanation for our findings is that liberal voters are simply creating more diverse councils in the at-large elections when they have the opportunity to select more than one candidate—choosing Asian or Latino candidates rather than black candidates among some of the three candidates they choose. We test this possibility by focusing on elections in which only one black candidate appeared. If our liberals are actually making more diverse slates, and are not affected by cognitive processing, the one black candidate should do equally well in district and at-large elections. This is not what we find. Instead, liberals are significantly less likely to choose the one black candidate in at-large elections than in district elections – with an effect size even larger than in the full sample. The coefficient on black candidates interacted with at-large elections is − 0.19 (SE = 0.07) in this subset of the data compared to − 0.07 (SE = 0.039) in the full sample.

  23. This finding that black candidates do better in district elections is consistent with existing research outside of the experimental lab. Racial and ethnic minorities are more likely to achieve descriptive representation in real district (as opposed to at-large) elections as well (Marschall et al. 2010). To date, scholars have argued this effect is a product of geographic segregation (e.g., Trounstine and Valdini 2008; Sass 2000; Vedlitz and Johnson 1982). However, our results indicate that geography may not be the sole reason for this pattern. Districts may enhance descriptive representation of racial and ethnic minorities for an additional reason: the ease of decision making in a race with fewer candidates.

References

  • Allport, G. W. (1954). The nature of prejudice. Oxford: Addison-Wesley.

    Google Scholar 

  • Anzia, S. (2014). Timing and turnout: How Off-cycle elections favor organized groups. Chicago: University of Chicago Press.

    Google Scholar 

  • Berinsky, A., Huber, G., & Lenz, G. (2012). Evaluating online labor markets for experimental research: Amazon.com’s mechanical turk. Political Analysis,20(3), 351–368.

    Google Scholar 

  • Berinsky, A. J., Hutchings, V. L., Mendelberg, T., Shaker, L., & Valentino, N. A. (2011). Sex and race: Are Black candidates more likely to be disadvantaged by sex scandals? Political Behavior,33(2), 179–202. https://doi.org/10.1007/s11109-010-9135-8.

    Article  Google Scholar 

  • Berinsky, A. J., & Mendelberg, T. (2005). The indirect effects of discredited stereotypes in judgments of Jewish leaders. American Journal of Political Science,49(4), 845–864.

    Google Scholar 

  • Berry, C. (2009). Imperfect union: Representation and taxation in multilevel governments. New York: Cambridge University Press.

    Google Scholar 

  • Blair, I. V. (2002). The malleability of automatic stereotypes and prejudice. Personality and Social Psychology Review,6(3), 242–261. https://doi.org/10.1207/S15327957PSPR0603_8.

    Article  Google Scholar 

  • Blake, A. (2017). Republicans’ views of blacks’ intelligence, work ethic lag behind Democrats at a record clip. Washington Post. March 31, 2017. https://www.washingtonpost.com/news/the-fix/wp/2017/03/31/the-gap-between-republicans-and-democrats-views-of-african-americans-just-hit-a-new-high/?utm_term=.63f0090b9bf2.

  • Bobo, L., Charles, C., Krysan, M., & Simmons, A. (2012). The real record on racial attitudes. In P. Marsden (Ed.), Social trends in American life: Findings from the general social survey since 1972 (pp. 38–83). Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Bodenhausen, G. V. (1990). Stereotypes as judgmental heuristics: Evidence of circadian variations in discrimination. Psychological Science,1, 319–322.

    Google Scholar 

  • Broockman, D., Carnes, N., Crowder-Meyer, M., & Skovron, C. (2014). Who’s a good candidate? How party gatekeepers evaluate potential nominees. Paper presented at the Annual Meeting of the American Political Science Association, Washington DC.

  • Buckley, F., Collins, N., & Reidy, T. (2007). Ballot paper photographs and low-information elections in Ireland. Politics,27(3), 174–181.

    Google Scholar 

  • Burdein, I., Lodge, M., & Taber, C. (2006). Experiments on the automaticity of political beliefs and attitudes. Political Psychology,27(3), 359–371.

    Google Scholar 

  • Caruso, E. M., Mead, N. L., & Balcetis, E. (2009). Political partisanship influences perception of biracial candidates’ skin tone. Proceedings of the National Academy of Sciences United States of America,106(48), 20168–20173.

    Google Scholar 

  • Conover, P. J., & Feldman, S. (1989). Candidate perception in an ambiguous world: Campaigns, cues, and inference processes. American Journal of Political Science,33(4), 912–940.

    Google Scholar 

  • Crandall, C., & Eshleman, A. (2003). A justification-supression model of the expression and experience of prejudice. Psychological Bulletin,129(3), 414–446.

    Google Scholar 

  • Crowder-Meyer, M., Gadarian, S., & Trounstine, J. (2017). Voting can be hard information helps. Paper Presented at the Annual Meeting of the Midwest Political Science Association, Chicago, IL.

  • Devine, P. G., & Monteith, M. J. (1993). The role of discrepancy associated affect in prejudice reduction. In D. M. Mackie & D. L. Hamilton (Eds.), Affect, cognition, and stereotyping (pp. 317–344). New York: Academic Press.

    Google Scholar 

  • Ditonto, T. M., Lau, R. R., & Sears, D. O. (2013). AMPing racial attitudes: Comparing the power of explicit and implicit racism measures in 2008. Political Psychology,34, 487–510. https://doi.org/10.1111/pops.12013.

    Article  Google Scholar 

  • Dovidio, J., & Gaertner, S. (2000). Aversive racism and selection decisions: 1989 and 1999. Psychological Science,11(4), 315–319.

    Google Scholar 

  • Dovidio, J., & Gaertner, S. (2004). Aversive racism. Advances in Experimental Social Psychology,36, 1–52.

    Google Scholar 

  • Downs, A. (1957). An economic theory of democracy. New York: Harper.

    Google Scholar 

  • Evans, J. S. (2008). Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology,59, 255–278.

    Google Scholar 

  • Fitzsimons, G. J., & Williams, P. (2000). Asking questions can change choice behavior: Does it do so automatically or effortfully? Journal of Experimental Psychology: Applied,6(3), 195–206.

    Google Scholar 

  • Galdi, S., Arcuri, L., & Gawronski, B. (2008). Automatic mental associations predict future choices of undecided decision-makers. Science,321(5892), 1100–1102.

    Google Scholar 

  • Garbarino, E., & Edell, J. (1997). Cognitive effort, affect, and choice. Journal of Consumer Research,24(2), 147–158.

    Google Scholar 

  • Gilbert, D. T., & Hixon, J. G. (1991). The trouble of thinking: Activation and application of stereotypic beliefs. Journal of Personality and Social Psychology,60, 509–517.

    Google Scholar 

  • Gilens, M. (1999). Why Americans hate welfare: Race, media, and the politics of antipoverty policy. Chicago: University of Chicago Press.

    Google Scholar 

  • Hainmueller, J., Hopkins, D. J., & Yamamoto, T. (2014). Causal inference in conjoint analysis: Understanding multidimensional choices via stated preference experiments. Political Analysis,22(1), 1–30.

    Google Scholar 

  • Howell, S. (1994). Racism, cynicism, economics, and david duke. American Politics Research,22(2), 190–207.

    Google Scholar 

  • Huckfeldt, R., Levine, J., Morgan, W., & Sprague, J. (1999). Accessibility and the political utility of partisan and ideological orientations. American Journal of Political Science,43(3), 888–911.

    Google Scholar 

  • Huddy, L., & Feldman, S. (2009). On assessing the political effects of racial prejudice. Annual Review of Political Science,12, 423–447.

    Google Scholar 

  • Huff, C., & Tingley, D. (2015). Who are these people? Evaluating the demographic characteristics and political preferences of MTurk survey respondents. Research & Politics,2(3), 2053168015604648.

    Google Scholar 

  • Hutchings, V., & Valentino, N. (2004). The centrality of race in American politics. Annual Review of Political Science,7, 383–408.

    Google Scholar 

  • Jacobsmeier, M. L. (2015). From Black and White to left and right: Race, perceptions of candidates’ ideologies, and voting behavior in U.S. house elections. Political Behavior,37(3), 595–621. https://doi.org/10.1007/s11109-014-9283-3.

    Article  Google Scholar 

  • Jamieson, D. W., & Zanna, M. P. (1989). Need for structure in attitude formation and expression. In A. R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude structure and function (pp. 383–406). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Jones, P. E. (2013). Revisiting stereotypes of non-white politicians’ ideological and partisan orientations. American Politics Research,42(2), 283–310. https://doi.org/10.1177/1532673X13498266.

    Article  Google Scholar 

  • Juenke, E. G., & Shah, P. (2015). Not the usual story: The effect of candidate supply on models of Latino descriptive representation. Politics, Groups, and Identities,3(3), 438–453.

    Google Scholar 

  • Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist,58(9), 697–720. https://doi.org/10.1037/0003-066X.58.9.697.

    Article  Google Scholar 

  • Kalmoe, N. P., & Piston, S. (2013). Is implicit prejudice against blacks politically consequential? Evidence from the AMP. Public Opinion Quarterly,77(1), 305–322.

    Google Scholar 

  • Kam, C. D. (2007). Implicit attitudes, explicit choices: When subliminal priming predicts candidate preference. Political Behavior,29(3), 343–367.

    Google Scholar 

  • Kao, G. (1995). Group images and possible selves among adolescents: Linking stereotypes to expectations by race and ethnicity. Sociological Forum,15(3), 407–430.

    Google Scholar 

  • Kinder, D. R., & Kam, C. D. (2010). Us against them: Ethnocentric foundations of American opinion. Chicago: The University of Chicago Press.

    Google Scholar 

  • Kinder, D., & Ryan, T. (2017). Prejudice and politics re-examined the political significance of implicit racial bias. Political Science Research and Methods,5(2), 241–259. https://doi.org/10.1017/psrm.2015.49.

    Article  Google Scholar 

  • Kinder, D., & Sanders, L. (1996). Divided by color. Chicago: University of Chicago Press.

    Google Scholar 

  • Kirkland, P., & Coppock, A. (2018). Candidate choice without partisan labels: New insights from conjoint survey experiments. Political Behavior,40(3), 571–591.

    Google Scholar 

  • Krumpal, I. (2013). Determinants of social desirability bias in sensitive surveys: A literature review. Quality & Quantity,47(4), 2025–2047.

    Google Scholar 

  • Kunda, Z., Davies, P., Hoshino-Browne, E., & Jordan, C. (2003). The impact of comprehension goals on the ebb and flow of stereotype activation during interaction. In S. J. Spencer, S. Fein, M. P. Zanna, & J. M. Olson (Eds.), Motivated social perception: The Ontario symposium (Vol. 9, pp. 1–20). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Kunda, Z., & Spencer, S. J. (2003). When do stereotypes come to mind and when do they color judgment? A goal-based theoretical framework for stereotype activation and application. Psychological Bulletin,129(4), 522.

    Google Scholar 

  • Lau, R. R., & Redlawsk, D. P. (2006). How voters decide: Information processing in election campaigns. Cambridge: Cambridge University Press.

    Google Scholar 

  • Lawless, J. L. (2011). Becoming a candidate: Political ambition and the decision to run for office. Cambridge: Cambridge University Press.

    Google Scholar 

  • Lawson, C., Lenz, G., Baker, A., & Myers, M. (2010). Looking like a winner: Candidate appearance and electoral success in new democracies. World Politics,62(4), 561–593.

    Google Scholar 

  • Lodge, M., & Charles, T. (2000). Three steps toward a theory of motivated political reasoning. In A. Lupia, M. D. McCubbins, & S. L. Popkin (Eds.), Elements of reason (pp. 183–213). Cambridge: Cambridge University Press.

    Google Scholar 

  • Lodge, M., & Taber, C. (2005). The automaticity of affect for political leaders, groups, and issues: An experimental test of the hot cognition hypothesis. Political Psychology,26(3), 455–482.

    Google Scholar 

  • Lupia, A. (1992). Busy voters, agenda control and the power of information. American Political Science Review,86(2), 390–403.

    Google Scholar 

  • Lupia, A. (1994). Shortcuts versus encyclopedias: Information and voting behavior in California insurance reform elections. American Political Science Review,88(1), 63–76.

    Google Scholar 

  • Lupia, A., & McCubbins, M. (1998). The democratic dilemma. New York: Cambridge University Press.

    Google Scholar 

  • Marschall, M. J., Ruhil, A. V., & Shah, P. R. (2010). The new racial calculus: Electoral institutions and black representation in local legislatures. American Journal of Political Science,54(1), 107–124.

    Google Scholar 

  • McDermott, M. L. (1997). Voting cues in low-information elections: Candidate gender as a social information variable in contemporary United States elections. American Journal of Political Science.,41(1), 270–283.

    Google Scholar 

  • McDermott, M. L. (1998). Race and gender cues in low-information elections. Political Research Quarterly,51(4), 895–918.

    Google Scholar 

  • Mendelberg, T. (2001). The race card: Campaign strategy, implicit messages, and the norm of equality. Princeton: Princeton University Press.

    Google Scholar 

  • Mo, C. (2015). The consequences of explicit and implicit gender attitudes and candidate quality in the calculations of voters. Political Behavior,37(2), 357–395.

    Google Scholar 

  • Moskowitz, G. B., Gollwitzer, P. M., Wasel, W., & Schaal, B. (1999). Preconscious control of stereotype activation through chronic egalitarian goals. Journal of Personality and Social Psychology,77(1), 167.

    Google Scholar 

  • Nosek, B. A., Smyth, F. L., Hansen, J. J., Devos, T., Lindner, N. M., Ranganath, K. A., et al. (2007). Pervasiveness and correlates of implicit attitudes and stereotypes. European Review of Social Psychology,18(1), 36–88.

    Google Scholar 

  • Oliver, J. Eric. (2012). Local elections and the politics of small scale democracy. Princeton: Princeton University Press.

    Google Scholar 

  • Olivola, C. Y., & Todorov, A. (2010). Elected in 100 milliseconds: Appearance-based trait inferences and voting. Journal of Nonverbal Behavior,34(2), 83–110.

    Google Scholar 

  • Payne, B. Keith, Krosnick, J. A., Pasek, J., Lelkes, Y., Akhtar, O., & Tompson, T. (2010). Implicit and explicit prejudice in the 2008 American presidential election. Journal of Experimental Social Psychology,46(2), 367–374.

    Google Scholar 

  • Peffley, M., & Shields, T. (1996). Whites’ stereotypes of African Americans and their impact on contemporary political atittudes. In M. X. Delli-Carpini, L. Huddy, & R. Y. Shapiro (Eds.), Research in micropolitics: Rethinking rationality (pp. 179–209). Greenwich, CT: JAI Press.

    Google Scholar 

  • Perez, E. O. (2010). Explicit evidence on the import of implicit attitudes: The IAT and immigration policy judgments. Political Behavior,32(4), 517–545.

    Google Scholar 

  • Pew Research Center. (2010). “Millennials: A portrait of generation next. Confident. Connected. Open to Change.” Pew Research Center. Retrieved June 27, 2016 from http://www.pewsocialtrends.org/files/2010/10/millennials-confident-connected-open-to-change.pdf.

  • Popkin, S. (1994). The reasoning voter: Communication and persuasion in presidential campaigns. Chicago: University of Chicago Press.

    Google Scholar 

  • Pratto, F., & Bargh, J. A. (1991). Stereotyping based on apparently individuating information: Trait and global components of sex stereotypes under attention overload. Journal of Experimental Social Psychology,27(1), 26–47.

    Google Scholar 

  • Rahn, W. M. (1993). The role of partisan stereotypes in information processing about political candidates. American Journal of Political Science,37(2), 472–496.

    Google Scholar 

  • Riggle, E. D., Ottati, V. C., Wyer, R. S., Kuklinski, J., & Schwarz, N. (1992). Bases of political judgments: The role of stereotypic and nonstereotypic information. Political Behavior,14(1), 67–87.

    Google Scholar 

  • Sass, T. R. (2000). The determinants of hispanic representation in municipal government. Southern Economic Journal,66(3), 609–630.

    Google Scholar 

  • Schaffner, B., Streb, M., & Wright, G. (2001). Teams without uniforms: The nonpartisan ballot in state and local elections. Political Research Quarterly,54(1), 7–30.

    Google Scholar 

  • Schuman, H., Steeh, C., Bobo, L., & Krysan, M. (1997). Racial attitudes in America: Trends and interpretations. Cambridge: Harvard University Press.

    Google Scholar 

  • Sears, D., & Citrin, J. (1985). Tax revolt: Something for nothing in California. Cambridge: Harvard University Press.

    Google Scholar 

  • Sears, D. O., & Henry, P. J. (2003). The origins of symbolic racism. Journal of Personality and Social Psychology,85(2), 259–275.

    Google Scholar 

  • Sechrist, G. B., & Stangor, C. (2001). Perceived consensus influences intergroup behavior and stereotype accessibility. Journal of Personality and Social Psychology,80, 645–654.

    Google Scholar 

  • Sinclair, L., & Kunda, Z. (1999). Reactions to a Black professional: Motivated inhibition and activation of conflicting stereotypes. Journal of Personality and Social Psychology,77, 885–904.

    Google Scholar 

  • Sniderman, P. M., & Piazza, T. (1993). The scar of race. Cambridge: Belknap Press of Harvard University Press.

    Google Scholar 

  • Spencer, S. J., Fein, S., Wolfe, C. T., Fong, C., & Dunn, M. A. (1998). Automatic activation of stereotypes: The role of self-image threat. Personality and Social Psychology Bulletin,24, 1139–1152.

    Google Scholar 

  • Stern, C., Balcetis, E., Cole, S., West, T. V., & Caruso, E. M. (2016). Government instability shifts skin tone representations of and intentions to vote for political candidates. Journal of Personality and Social Psychology,110(1), 76.

    Google Scholar 

  • Swigger, N. (2012). What you see is what you get: Drawing inferences from campaign imagery. Political Communication,29(4), 367–386.

    Google Scholar 

  • Tesler, M. (2012). The spillover of racialization into health care: How President Obama polarized public opinion by racial attitudes and race. American Journal of Political Science,56(3), 690–704.

    Google Scholar 

  • Tesler, M. (2016). Post-racial or most-racial?: Race and politics in the Obama era. Chicago: University of Chicago Press.

    Google Scholar 

  • Todorov, A., Mandisodza, A., Goren, A., & Hall, C. (2005). Inferences of competence from faces predict election outcomes. Science,308(5728), 1623–1626.

    Google Scholar 

  • Trounstine, J. (2008). Political monopolies in American Cities: the rise and fall of bosses and reformers. Chicago: University of Chicago Press.

    Google Scholar 

  • Trounstine, J., & Valdini, M. (2008). The context matters: The effects of single member versus at-large districts on city council diversity. American Journal of Political Science,53(3), 554–569.

    Google Scholar 

  • Ülkümen, G., Thomas, M., & Morwitz, V. G. (2008). Will I spend more in 12 months or a year? The effect of ease of estimation and confidence on budget estimates. Journal of Consumer Research,35(2), 245–256.

    Google Scholar 

  • Valentino, N., Neuner, F. G., & Vandenbroek, L. M. (2018). The changing norms of racial political rhetoric and the end of racial priming. The Journal of Politics,80(3), 757–771. https://doi.org/10.1086/694845.

    Article  Google Scholar 

  • Vedlitz, A., & Johnson, C. (1982). Community racial concentration, electoral structure, and minority representation. Social Science Quarterly,63(4), 729–736.

    Google Scholar 

  • Weaver, V. M. (2012). The electoral consequences of skin color: The ‘hidden’ side of race in politics. Political Behavior,34(1), 159–192. https://doi.org/10.1007/s11109-010-9152-7.

    Article  Google Scholar 

  • Yadon, N., & Piston, S. (2018). Examining whites’ anti-black attitudes after Obama’s presidency. Politics, Groups, and Identities. https://doi.org/10.1080/21565503.2018.1438953.

    Article  Google Scholar 

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Acknowledgements

Thank you to participants at Princeton University, Simon Fraser University, University of British Columbia, University of Michigan, Cornell University, MPSA 2016, and APSA 2016 for comments.

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Crowder-Meyer, M., Gadarian, S.K., Trounstine, J. et al. A Different Kind of Disadvantage: Candidate Race, Cognitive Complexity, and Voter Choice. Polit Behav 42, 509–530 (2020). https://doi.org/10.1007/s11109-018-9505-1

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