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Rebuttals as deracializing strategies for African American and white candidates

Published online by Cambridge University Press:  05 November 2020

Matthew Tokeshi*
Affiliation:
Williams College, Schapiro Hall Room 238, 24 Hopkins Hall Drive, Williamstown, MA 01267, USA
*
Corresponding author. E-mail: mt13@williams.edu

Abstract

The study of American racial politics has long focused on the conditions that activate racial animosity. A central line of research demonstrates that campaign messages that highlight negative stereotypes of African Americans can activate whites' racial attitudes. However, little is known about whether this activation can be overcome. I develop a theory of racial deactivation and test its predictions with two survey experiments. I find that explicitly criticizing the racial nature of an attack restores support for white candidates, but not African American candidates. However, African American and white candidates fare equally well using two rebuttal styles: a credible, non-racial justification of the attacked action or an explicit racial critique combined with the justification. The results have implications for how race affects campaigns, the susceptibility of the American public to racial cues, and campaign strategy.

Information

Type
Research Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of The Race, Ethnicity, and Politics Section of the American Political Science Association
Figure 0

Figure 1. Experimental design (Note: While the target's race is either black or white, the criminal's race is black in all conditions).

Figure 1

Figure 2. Two versions of the attack news story, black target (left) and white target (right). The text of the news story is shown in Figure 1 of the Appendix.

Figure 2

Table 1. Description of rebuttal stories

Figure 3

Figure 3. The impact of rebuttals on target-attacker evaluations. Positive values indicate that the rebuttal helped the target. Error bars represent 84% confidence intervals, which is consistent with a two-tailed test of overlap at p = 0.05. In other words, values are significantly different where error bars do not overlap. The “rebuttal effect” is the average change in target-attacker rating from post-attack to post-rebuttal for each rebuttal.

Figure 4

Figure 4. Rebuttal effects among high racial resentment respondents only (top third of the sample, corresponding with racial resentment ⩾0.6875 on a 0–1 scale). Positive values indicate that the rebuttal helped the target. Error bars represent 84% confidence intervals, which is consistent with a two-tailed test of overlap at p = 0.05. In other words, values are significantly different where error bars do not overlap.

Figure 5

Figure 5. Rebuttal effects among low racial resentment respondents only (bottom third of the sample, corresponding with racial resentment ⩽0.5 on a 0–1 scale). Positive values indicate that the rebuttal helped the target. Error bars represent 84% confidence intervals, which is consistent with a two-tailed test of overlap at p = 0.05. In other words, values are significantly different where error bars do not overlap.

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