Race, Gender and the US Presidency: A Comparison of Implicit and Explicit Biases in the Electorate

Gemma Anne Calvert (Lead / Corresponding author), Geoffrey Evans, Abhishek Pathak

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
97 Downloads (Pure)

Abstract

Recent U.S. elections have witnessed the Democrats nominating both black and female presidential candidates, as well as a black and female vice president. The increasing diversity of the U.S. political elite heightens the importance of understanding the psychological factors influencing voter support for, or opposition to, candidates of different races and genders. In this study, we investigated the relative strength of the implicit biases for and against hypothetical presidential candidates that varied by gender and race, using an evaluative priming paradigm on a broadly representative sample of U.S. citizens (n = 1076). Our main research question is: Do measures of implicit racial and gender biases predict political attitudes and voting better than measures of explicit prejudice? We find that measures of implicit bias are less strongly associated with political attitudes and voting than are explicit measures of sexist attitudes and modern racism. Moreover, once demographic characteristics and explicit prejudice are controlled statistically, measures of implicit bias provide little incremental predictive validity. Overall, explicit prejudice has a far stronger association with political preferences than does implicit bias.
Original languageEnglish
Article number17
Number of pages10
JournalBehavioral Sciences
Volume12
Issue number1
DOIs
Publication statusPublished - 17 Jan 2022

Keywords

  • implicit bias
  • evaluative priming
  • sexism
  • racism
  • political identity
  • voting
  • Sexism
  • Voting
  • Implicit bias
  • Evaluative priming
  • Racism
  • Political identity

ASJC Scopus subject areas

  • General Psychology
  • Development
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Behavioral Neuroscience

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