Is Sexism for White People? Gender Stereotypes, Race, and the 2016 Presidential Election

Abstract

On November 8, 2016 Donald Trump, a man with no office-holding experience, won the Electoral College, defeating the first woman to receive the presidential nomination from a major party. This paper offers the first observational test of how sexism affects presidential vote choice in the general election, adding to the rich literature on gender and candidate success for lower-level offices. We argue that the 2016 election implicated gender through Hillary Clinton’s candidacy and Donald Trump’s sexist rhetoric, and activated gender attitudes such that sexism is associated with vote choice. Using an Election Day exit poll survey of over 1300 voters conducted at 12 precincts in a mid-size city and a national survey of over 10,000 White and Black Americans, we find that a politically defined measure of sexism—the belief that men are better suited emotionally for politics than women—predicts support for Trump both in terms of vote choice and favorability. We find the effect is strongest and most consistent among White voters. However, a domestically defined measure of sexism—whether men should be in control of their wives—offers little explanatory power over the vote. In total, our results demonstrate the importance of gender in the 2016 election, beyond mere demographic differences in vote choice: beliefs about gender and fitness for office shape both White men and women’s preferences.

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Notes

  1. 1.

    The majority of Muslim Americans are White, but they comprise a small segment of the overall population. Therefore we do not expect the inclusion of any Muslim Americans among White respondents to seriously change any results.

  2. 2.

    A recent FiveThirtyEight article identified Oklahoma City as one of the ten metropolitan areas that most closely match national demographics (age, educational attainment, race, and ethnicity) in the country (Kolko 2016).

  3. 3.

    Undergraduate students received course credit for completing CITI training, attending three instructional sessions, surveying on Election Day, and attending a data entry session. Altogether, students received between 10 and 12 hours of instruction. While we were at the polling locations all day, undergraduates typically recruited respondents for 2–4 hours each. In field training students practiced random selection, learned when to direct a participant toward one of the authors, and practiced interacting with respondents. The latter was instrumental in resolving pollster idiosyncrasies, with the aim of consistent survey delivery.

  4. 4.

    The lower proportion of Latinos in the Latino precincts is relatively unsurprising given the lower rate of Latino turnout (Krogstad et al. 2016) and the relatively recent immigration history in the city.

  5. 5.

    We categorize respondents’ race from a mark-one-or-more measure. This measure included Hispanic/Latino as a racial category. From there, we identify respondents with a singular racial category if that is the only group they marked. Respondents who selected more than one category are coded as “Mixed race” given recent research on the political uniqueness of those who identify with two or more racial groups (Davenport 2016).

  6. 6.

    We measure party registration rather than party ID so that we can examine the quality of our sample against the known population parameters from party registration statistics for each precinct.

  7. 7.

    Ideally, we would specify models for each racial group separately, however the sample sizes for each non-White racial group are too small.

  8. 8.

    That the effects of sexism would be independent from other anti-outgroup attitudes is not unexpected, as the structure of the gender schema does not rely on the same social segregation and negative feelings toward outgroups that structure the racial schema. Instead, gender schemas are built on intimate contact between men and women and feelings of mutual dependence (Huddy and Carey 2009; Ridgeway 2011; Winter 2008).

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Acknowledgements

We thank Matt Barreto, Caroline Heldman, Nazita Lajevardi, Hannah Walker, and the participants of the UCLA May 2017 mini-conference for their thoughtful and instructive comments. We are grateful to David Rudd Ross for his careful reading. Thank you to Matt Barreto and Loren Collingwood for their efforts and organization. We greatly appreciate Skip Lupia’s helpful advice on training students to interview voters. We are indebted to Keith Gaddie and the College of Arts & Sciences for their support in developing the Community Engagement + Experiments Lab at the University of Oklahoma. We thank Joy Pendley for her leadership with CEEL. We are grateful to Doug Sanderson and the Oklahoma County Election Board for their willingness to work with researchers. Thanks to Alisa Hicklin Fryar and Tyler Johnson for their sage advice. Finally, thank you to the more than sixty undergraduate and graduate students who spent their day surveying voters and to Cathy Brister, Katelyn Burks, David Rudd Ross, and Jamie Vaughn for their field support.

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Correspondence to Mackenzie Israel-Trummel.

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Data and replication files are available at http://dx.doi.org/10.7910/DVN/XTJRQN

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Bracic, A., Israel-Trummel, M. & Shortle, A.F. Is Sexism for White People? Gender Stereotypes, Race, and the 2016 Presidential Election. Polit Behav 41, 281–307 (2019). https://doi.org/10.1007/s11109-018-9446-8

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Keywords

  • Presidential vote
  • Sexism
  • Gender
  • Race
  • Exit poll