Racial Prejudice, Partisanship, and White Turnout in Elections with Black Candidates

Abstract

How does racial prejudice affect White turnout in elections with Black candidates? Previous research, which largely focuses on the relationship between prejudice and vote choice, rarely examines the relationship between prejudice and turnout, leading to an incomplete picture of the impact of prejudice on the fate of Black candidates. In this project, we examine a key condition under which partisanship and partisan strength moderate the effect of prejudice on electoral behavior. Specifically, we argue that when a prejudiced strong partisan shares the partisanship of a Black candidate, she is likely to experience a decision conflict—prejudice and partisanship point in opposing directions—increasing the likelihood that she stays home on Election Day. We test this argument through observational analyses of the 2008 presidential election. Our findings illuminate an additional barrier to Black electoral representation: racial prejudice undermines Black candidates’ efforts to mobilize strong partisans.

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Fig. 1
Fig. 2

Notes

  1. 1.

    Based on reports from the Joint Center for Political and Economic Studies. Although the Joint Center shows a consistent, linear increase in Black elected officials at the local and state levels, the increases in the number of Black elected officials in the national House of Representatives and Senate are more minimal. In particular, at the national level since 1970 the only substantial increases in the number of Black elected officials occur in 1983 (a 16.7 % change) and 1987 (15.0 % change). Aside from these two years, the changes in the number of Black elected officials do not show a consistent or substantively large increase. Indeed, in some years the number of Black elected officials actually decreases at the national level.

  2. 2.

    As Weaver (2012) points out, “prior studies have … avoided party labels because of their potential to ‘swamp’ the results.”

  3. 3.

    The difference between a decision conflict and cognitive dissonance is that while a decision conflict is an individual’s inability to select between two equally important decision attributes, cognitive dissonance is the feeling of discomfort and tension which often arises from actually making the choice and selecting one decision alternative at the expense of the other. As a result, while some decision conflicts can produce cognitive dissonance, this is most likely to happen if an individual actually works to overcome the conflict and make a choice (Cummings and Venkatesan 1976). In our particular case, we will be considering cases where individuals cannot overcome decision conflicts.

  4. 4.

    Pasek et al. (2009) examine both vote choice and turnout, although their analysis does not specifically consider White individuals or the conditioning role of partisanship and partisan strength on the effect of prejudice.

  5. 5.

    Throughout the manuscript, given that our hypotheses are directional, all hypothesis tests are one-tailed.

  6. 6.

    Since we rely on a self-reported measure of voter turnout, it is worth noting that there is a possibility that over-reporting will affect the results. The extent to which over-reporting of turnout occurs is the subject of recent debate (Ansolabehere and Hersh 2012; Berent et al. 2011). If anything, we suspect that over-reporting results in a more conservative test; strong Democrats are more likely to falsely report voting (Belli et al. 2001), which may bias our estimates of the effect of prejudice on turnout among strong Democrats toward zero.

  7. 7.

    While this finding is suggestive, it is not dispositive. Interaction terms in logistic regressions do not account for an additional potential interaction resulting from the imposition of the sigmoidal function (Kam and Franzese 2007). The marginal effects plots are therefore better suited to show the differential effects of prejudice on turnout for strong Democrats and other Whites.

  8. 8.

    Given the various contextual factors that can influence prejudice, it is possible that some of the control variables are not causally prior to our critical variables; we thank an anonymous reviewer for raising this issue.

  9. 9.

    In order to estimate the total impact of prejudice on White strong Democrats, we also compare the mean predicted probability of turning out to vote using the independent variables’ actual values to the mean predicted probability of turning out to vote after setting the stereotype index to its midpoint, at which no prejudice is expressed. Using this method, we estimate that racial prejudice decreased turnout by 4 percentage points (from 91 to 87 %).

  10. 10.

    We obtain similar patterns when we estimate the marginal effects of an increase in prejudice using models where no controls are included. Using a model that includes all Whites, for example, an increase in prejudice among strong Democrats decreases the chance of turnout by 42 percentage points; an effect significant at p < 0.05 (one tailed). Among those who are not strong Democrats, an increase in prejudice has a null effect on turnout (+0.04 %, not significant).

  11. 11.

    We also estimate a version of Model 5 with the inclusion of candidate affect as a control, calculated as the differential between the thermometer scores for Obama and McCain. Our results are robust to the inclusion of this additional variable; the coefficient on the interaction is 5.45 (2.35), p < 0.05 (one-tailed).

  12. 12.

    See http://www.knowledgenetworks.com/ganp/election2008 for more information.

  13. 13.

    According to Pasek et al. (2009), the dates and response rates of the AP-Yahoo-Stanford survey are as follows: “A total of 2,779 individuals were invited to complete the Wave 6 questionnaire (August 27–September 6, 2008), and 2,012 individuals did so (completion rate = 72.4 %; cumulative response rate CUMRR1 = 10.4 %; see Callegaro and DiSagra 2008). 2,698 individuals were invited to complete the Affect Misattribution Procedure (August 27–September 6, 2008), and 1,688 of them did so (completion rate = 62.6 %; CUMRR1 = 9.2 %). A total of 2,742 individuals were invited to complete Wave 10 (November 4–18, 2008), and 1,989 did so (completion rate = 72.5 %, CUMRR1 = 10.4 %). 1,762 individuals who completed Wave 6 also reported turnout and candidate choice postelection.

  14. 14.

    The question wording is as follows: “We’re interested in how people feel about various groups. Please tell us whether you have a favorable or unfavorable impression of each of the following groups” (Blacks are included among the groups presented). The response options are: Extremely favorable, Very favorable, Somewhat favorable, Neither favorable nor unfavorable, Somewhat unfavorable, Very unfavorable, and Extremely unfavorable.

  15. 15.

    Although we do not make any direct hypotheses about the size of the marginal effects in Fig. 2c, d, as well as e and f, we do follow Cumming and Fidler (2005) and compare these effects, which are statistically different.

  16. 16.

    Democrats: Increase in differential due to an increase in partisan strength at low levels of prejudice is 18.7, significant at p < 0.001 (one-tailed). Increase in differential due to an increase in partisan strength at high levels of prejudice is 6.5, p = 0.511 (one-tailed).

  17. 17.

    Republicans: Increase in differential due to an increase in partisan strength at low levels of prejudice is 15.0, significant at p < 0.001 (one-tailed). Increase in differential due to an increase in partisan strength at high levels of prejudice is 21.99, p < 0.05 (one-tailed).

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Acknowledgments

We thank Salma Al-Shami, Vincent L. Hutchings, John E. Jackson, Nathan Kalmoe, Georgia Kernell, Donald R. Kinder, Adam Seth Levine, Arthur Lupia, John Barry Ryan, and David C. Wilson for their helpful comments. We also thank participants at the 2010 Midwest Political Science Association Annual National Conference, especially Andra Gillespie and Shanna Pearson-Markowitz. Finally, we thank participants in the University of Michigan’s Interdisciplinary Workshop in American Politics, especially Charles Doriean, Ashley Jardina, Pamela Clouser McCann, and David Thomas Smith.

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Appendix 1: Variable Coding

Appendix 1: Variable Coding

Below we include our coding, the ANES variable number and, in cases where we considered multiple codings of the variable, we note the other ways in which the variable was coded to ensure overall robustness. The descriptive statistics are across the entire sample. Stata do-files available upon request.

Dependent variable (turnout): Coded 1 if voted (V085036x, voted = 76.3 %).

Partisan strength: Coded 1 if strong (V083098a, strong = 35.43 %).

Prejudice scale: Construction discussed in text; relies on differences in ratings of Whites (V083207a, V083208a) and Blacks (V083207b, V083208b, mean = 0.57, median = 0.54, SD = 0.11).

Age: In years, recoded 0–1 (V083215x, mean = 0.42, median = 0.41, SD = 0.23; when in years mean = 49.7, median = 49, SD = 17.5).

Education: Highest grade of school completed, from 0 to 17, recoded 0–1(V083217, mean = 0.81, median = 0.76, SD = 0.13; when 0–17 mean = 13.7, median = 13, SD = 2.21).

Gender: Coded 1 if female (V081101, men = 56.13 %).

Income: Categorical range from less than $2,999 to $150,000, recoded from 0 to 1 (V083249, mean = 0.45, median = 0.46, SD = 0.26).

Married: Coded 1 if currently married (V083216x, married = 49.10 %).

South: Coded 1 if respondent lives in one of the following states: Florida, South Carolina, Alabama, Mississippi, Georgia, Louisiana, Texas, Virginia, Arkansas, Tennessee and North Carolina. Results robust to the (a) exclusion of Florida and (b) inclusion of Kentucky and Oklahoma (V081201a, south = 38.8 %).

Interest: Higher value reflects more interest in politics. Results robust to use of only V085072 and to a combination of both V085072 and V085073a (mean = 0.61, median = 0.67, SD = 0.31).

Contacted by Party: Coded 1 if respondent was contacted by someone from a major party, 0 otherwise (V085025, contacted = 47.6 %).

Affect for Candidate (used only in a robustness check, see footnote 8): Differential between the Obama thermometer (V083037a) and McCain thermometer (V083037a) (mean = 15.65, SD = 46.5). Also robust to the absolute value of the differential (mean = 39.6, SD = 28.9).

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Krupnikov, Y., Piston, S. Racial Prejudice, Partisanship, and White Turnout in Elections with Black Candidates. Polit Behav 37, 397–418 (2015). https://doi.org/10.1007/s11109-014-9268-2

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Keywords

  • Race
  • Prejudice
  • Partisanship
  • Partisan strength
  • Turnout
  • Elections