Skip to main content

Advertisement

SpringerLink
Log in

But Can She Make America Great Again? Threat, Stability, and Support for Female Candidates in the United States

  • Original Paper
  • Published:
Political Behavior Aims and scope Submit manuscript

Abstract

Drawing on the literature on system justification, I argue that the fate of female candidates in the U.S. is tied to whether the election is occurring in relatively good or bad times. Using an original experiment embedded in the 2016 Cooperative Congressional Election Study, I show that exposure to low vs. high threat messages led to higher evaluations of Hillary Clinton. These findings are complimented by a vote choice model that shows that the likelihood of supporting Clinton over Trump was significantly higher when perceived threat (as captured by economic assessments) was lower. A second original experiment better isolates the effects of candidate sex and generalizes these findings beyond the 2016 case. These results highlight the importance of including campaign context in studies of candidate evaluation and suggest that overt sexism is not the only hurdle facing women running for office in the U.S.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.

Similar content being viewed by others

Notes

  1. Principal Investigators Stephen Ansolabehere and Brian Schaffner. For more detail, see https://cces.gov.harvard.edu/.

  2. In the 116th Congress, men outnumber women 333 to 102 in the House and 75 to 25 in the Senate.

  3. This temporal dynamic may also shed some light on the differences between the Azavedo et al. (2017) and Weinschenk and Dawes (2019) findings, as the survey in the former was fielded prior to the survey in the latter.

  4. Data and code to replicate all analyses presented in this article are publicly available at https://doi.org/10.7910/DVN/IONQ8V.

  5. Though these treatments effectively manipulate threat, they are perhaps more mild than some of the actual rhetoric and threat messaging used in the 2016 campaign. I thank an anonymous reviewer for raising this point and return to it in the concluding discussion.

  6. The order in which the four items were shown to respondents was randomized.

  7. See Hoffman and Hurst (1990) and Jost and Kay (2005).

  8. For sample characteristics across treatments, see Online Appendix A.

  9. Nonvoters and those who reported voting for a different candidate are omitted.

  10. Manipulation checks in both studies showed that those in the instability condition were significantly less likely to view the current economy as stable.

  11. These include partisanship, ideological identification, sex, age, education, race, family income, and residency in a southern state.

  12. Modern sexism ranges from 1 to 5 (\(\stackrel{-}{X}\) = 2.27; s.d. = 1.22) and is the mean of agreement (on a 5-point scale) with the statements “Discrimination against women in the United States is no longer a problem” and “Women demanding equality are seeking special favors.” (α = .80). Traditional sexism is measured by agreement (on a 5-point scale) with the single item “It is better if a man works and a woman stays at home” (\(\stackrel{-}{X}\) = 2.15; s.d. = 1.25).

  13. The racial resentment index ranges from 1–6 (\(\stackrel{-}{X}\) = 2.16; s.d. = .97) and is the mean of agreement (on a 6-point scale) with three statements: (1) White people in the U.S. have certain advantages because of the color of their skin; (2) Racial problems in the U.S. are rare, isolated situations; and (3) I am angry that racism exists (α = .71).

  14. See the Online Appendix A for these results.

  15. Azevedo et al. (2017) report r = .52.

  16. See Online Appendix A.

  17. 17.53% of respondents are at or above the median of system justification, but below the median of modern sexism. Conversely, 14.64% of respondents are at or above the median of modern sexism but below the median of system justification. The pattern for traditional sexism is similar, as those same percentages are 21.39 and 18.88, respectively.

  18. The exception being Reny, Collingwood, and Valenzuela (2019), which includes a number of contextual economic indicators.

  19. Approval to work with human subjects in on file with the University of Houston. Details about the sample are available in Appendix B.

  20. Since the significant differences in my CCES findings were between these two treatments and not treatments and control, I omitted the control condition.

  21. Results of the pretest are available in Online Appendix B.

  22. The order in which these items were shown was also randomized.

  23. The mean ratings by treatment are available in Appendix B. These results show that across all treatments, Campbell has a slight advantage on both relative trait ratings (\(\stackrel{-}{X}\) = − .14) and vote share (50.67%). When looking across the various treatments, there does appear to be somewhat of a disconnect between trait evaluations and vote choice (i.e., Campbell receives higher ratings in 5 out of 6 cases but only has a higher vote percentage in 3 of the 6). These numbers likely reflect apparently lower levels of partisan bias in expressed vote choice. Indeed, while only 29.69% of partisans gave higher relative trait ratings to the candidate from the opposite party, 45.53% voted for the candidate from the opposite party. A full exploration of the causes of this difference is beyond the scope of this manuscript. I will, however, note that the questions were asked in different ways. Recall that vote choice was asked using wording which allows subjects to “save face” (Krupnikov et al. 2016). While this method is intended to lower social desirability pressure to support a female candidate, there may have been unintended effects on partisan bias. Such a possibility has not been tested, as the treatments used by Krupnikov et al. (2016) did not include party labels.

  24. For high system justifiers, the mean N for each of the twelve candidate X threat level groups is 54.17.

  25. Full transcript available here: https://www.politico.com/story/2016/07/full-transcript-donald-trump-nomination-acceptance-speech-at-rnc-225974.

References

  • Ashby, J., Ryan, M. K., & Haslam, S. A. (2006). Legal work and the glass cliff: Evidence that women are preferentially selected to lead problematic cases. William and Mary Journal of Women & Law, 13, 775–794.

    Google Scholar 

  • Azevedo, F., Jost, J. T., & Rothmund, T. (2017). ‘Making America great again’: System justification in the U.S. presidential election of 2016. Translational Issues in Psychological Science, 3(3), 231–240.

    Google Scholar 

  • Baker, W. D., & Oneal, J. R. (2001). Patriotism or opinion leadership? Journal of Conflict Resolution, 45(5), 661–687.

    Google Scholar 

  • Bartels, L. M. (2002). Beyond the running tally: Partisan bias in political perceptions. Political Behavior, 24(2), 117–150.

    Google Scholar 

  • Bauer, N. M. (2015). Emotional, sensitive, and unfit for office? Gender stereotype activation and support female candidates. Political Psychology, 36(6), 691–708.

    Google Scholar 

  • Berinsky, A. J. (2009). understanding american public opinion from World War II to Iraq. In Time of War.

  • Brown, E. R., & Diekman, A. B. (2013). Differential effects of female and male candidates on system justification: Can cracks in the glass ceiling foster complacency? European Journal of Social Psychology, 43(4), 299–306.

    Google Scholar 

  • Brown, E. R., Diekman, A. B., & Schneider, M. C. (2011). A change will do us good: Threats diminish typical preferences for male leaders. Personality and Social Psychology Bulletin, 37(7), 930–941.

    Google Scholar 

  • Cassese, E. C., & Holman, M. R. (2018). Playing the woman card: Ambivalent sexism in the 2016 U.S. presidential race. Political Psychology, 40(1), 55–74.

    Google Scholar 

  • Daily, C. M. (1995). The relationship between board composition and leadership structure and bankruptcy reorganization outcomes. Journal of Management, 21(6), 1041–1056.

    Google Scholar 

  • Dickerson, B. T., & Ondercin, H. L. (2017). Conditional motivated reasoning. Political Research Quarterly, 70(1), 194–208.

    Google Scholar 

  • Falk, E., & Kenski, K. (2006). Issue saliency and gender stereotypes: Support for women as presidents in times of war and terrorism. Social Science Quarterly, 87(1), 1–18.

    Google Scholar 

  • Frasure-Yokley, L. (2018). Choosing the velvet glove: Women voters, ambivalent sexism, and vote choice in 2016. Journal of Race, Ethnicity and Politics, 3(1), 3–25.

    Google Scholar 

  • Fritsche, I., & Jugert, P. (2017). The consequences of economic threat for motivated social cognition and action. Current Opinion in Psychology, 18, 31–36.

    Google Scholar 

  • Hambrick, D. C., & D’Aveni, R. A. (1992). Top team deterioration as part of the downward spiral of large corporate bankruptcies. Management Science, 38(10), 1445–1466.

    Google Scholar 

  • Haslam, S. A., & Ryan, M. K. (2008). The road to the glass cliff: Differences in the perceived suitability of men and women for leadership positions in succeeding and failing organizations. Leadership Quarterly, 19(5), 530–546.

    Google Scholar 

  • Hoffman, C., & Hurst, N. (1990). Gender stereotypes: Perception or rationalization? Journal of Personality and Social Psychology, 58(2), 197.

    Google Scholar 

  • Holman, M. R., Merolla, J. L., & Zechmeister, E. J. (2011). Sex, stereotypes, and security: A study of the effects of terrorist threat on assessments of female leadership. Journal of Women, Politics and Policy, 32(3), 173–192.

    Google Scholar 

  • Holman, M. R., Merolla, J. L., & Zechmeister, E. J. (2016). Terrorist threat, male stereotypes, and candidate evaluations. Political Research Quarterly, 69(1), 134–147.

    Google Scholar 

  • Hunyady, O., & Jost, J. T. (2002). The psychology of system justification and the palliative function of ideology. European Review of Social Psychology, 13(1), 111–153.

    Google Scholar 

  • Jones, P. E. (2019). Partisanship, political awareness, and retrospective evaluations, 1956–2016. Political Behavior. https://doi.org/10.1007/s11109-019-09543-y.

    Article  Google Scholar 

  • Jost, J. T. (2017). Working class conservatism: A system justification perspective. Current Opinion in Psychology, 18, 73–78.

    Google Scholar 

  • Jost, J. T., & Banaji, M. R. (1994). The role of stereotyping in system-justification and the production of false consciousness. British Journal of Social Psychology., 33(1), 1–27.

    Google Scholar 

  • Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 14(5), 260–265.

    Google Scholar 

  • Jost, J.T., & Hunyady, O. (2005). Antecedents and consequences of system-justifying ideologies. Current Directions in Psychological Science.

  • Jost, J. T., & Kay, A. C. (2005). Exposure to benevolent sexism and complementary gender stereotypes: Consequences for specific and diffuse forms of system justification. Journal of Personality and Social Psychology., 88(3), 498.

    Google Scholar 

  • Jost, J. T., et al. (2005). System-justifying functions of complementary regional and ethnic stereotypes: Cross-national evidence. Social Justice Research, 18(3), 305–333.

    Google Scholar 

  • Kam, C. D., & Simas, E. N. (2012). Risk attitudes, candidate characteristics, and vote choice. Public Opinion Quarterly, 76(4), 747–760.

    Google Scholar 

  • Kay, A. C., et al. (2009). Inequality, discrimination, and the power of the status quo: Direct evidence for a motivation to see the way things are as the way they should be. Journal of Personality and Social Psychology, 97(3), 421.

    Google Scholar 

  • Kay, A. C., & Friesen, J. (2011). On social stability and social change: Understanding when system justification does and does not occur. Current Directions in Psychological Science, 20(6), 360–364.

    Google Scholar 

  • Kay, A. C., & Jost, J. T. (2003). Complementary justice: Effects of ‘poor but happy’ and ‘poor but honest’ stereotype exemplars on system justification and implicit activation of the justice motive. Journal of Personality and Social Psychology, 85(5), 823.

    Google Scholar 

  • Kay, A. C., Jost, J. T., & Young, S. (2005). Victim derogation and victim enhancement as alternate routes to system justification. Psychological Science, 16(3), 240–246.

    Google Scholar 

  • Krupnikov, Y., & Bauer, N. M. (2014). The relationship between campaign negativity, gender and campaign context. Political Behavior, 36(1), 167–188.

    Google Scholar 

  • Krupnikov, Y., Piston, S., & Bauer, N. M. (2016). Saving face: Identifying voter responses to black candidates and female candidates. Political Psychology, 37(2), 253–273.

    Google Scholar 

  • Lau, G. P., Kay, A. C., & Spencer, S. J. (2008). Loving those who justify inequality: The effects of system threat on attraction to women who embody benevolent sexist ideals. Psychological Science.

  • Lawless, J. L. (2004). Women, war, and winning elections: Gender stereotyping in the post-september 11th Era. Political Research Quarterly, 57(3), 479–490.

    Google Scholar 

  • Lei, R. F., & Bodenhausen, G. V. (2018). Economic anxieties undermine support for female (but not male) political candidates. Analyses of Social Issues and Public Policy, 18(1), 244–264.

    Google Scholar 

  • Merolla, J. L., & Zechmeister, E. J. (2009). Terrorist threat, leadership, and the vote: Evidence from three experiments. Political Behavior, 31(4), 575–601.

    Google Scholar 

  • Merolla, J. L., Ramos, J. M., & Zechmeister, E. J. (2007). Crisis, charisma, and consequences: Evidence from the 2004 U.S. presidential election. Journal of Politics, 69(1), 30–42.

    Google Scholar 

  • Miller, A. L., & Borgida, E. (2019). The temporal dimension of system justification: Gender ideology over the course of the 2016 election. Personality and Social Psychology Bulletin, 45(7), 1057–1067.

    Google Scholar 

  • Milojev, P., Greaves, L., Osborne, D., & Sibley, C. G. (2015). Stability and change in political conservatism following the global financial crisis. Personality and Social Psychology Bulletin, 41(1), 127–139.

    Google Scholar 

  • Monteith, M. J., & Hildebrand, L. K. (2020). Sexism, perceived discrimination, and system justification in the 2016 U.S. presidential election context. Group Processes and Intergroup Relations, 23(2), 163–178.

    Google Scholar 

  • Mutz, D. C. (2018). Status threat, not economic hardship, explains the 2016 presidential vote. Proceedings of the National Academy of Sciences, 115(19), E4330–E4339.

    Google Scholar 

  • Oneal, J. R., & Bryan, A. L. (1995). The rally ’round the flag effect in U.S. foreign policy crises, 1950? 1985. Political Behavior, 17(4), 379–401.

    Google Scholar 

  • Ono, Y., & Burden, B. C. (2018). The contingent effects of candidate sex on voter choice. Political Behavior, 41(3), 583–607.

    Google Scholar 

  • Petrocik, J. R. (1996). Issue ownership in presidential elections, with a 1980 case study. American Journal of Political Science, 40, 825–850.

    Google Scholar 

  • Reny, T. T., Collingwood, L., & Valenzuela, A. A. (2019). Vote Switching in the 2016 election: How racial and immigration attitudes, not economics, explain shifts in white voting. Public Opinion Quarterly, 83(1), 91–113.

    Google Scholar 

  • Rudman, L. A., Moss-Racusin, C. A., Phelan, J. E., & Nauts, S. (2012). Status incongruity and backlash effects: Defending the gender hierarchy motivates prejudice against female leaders. Journal of Experimental Social Psychology, 48(1), 165–179.

    Google Scholar 

  • Ryan, M. K., & Haslam, S. A. (2005). The glass cliff: Evidence that women are over-represented in precarious leadership positions. British Journal of Management, 16(2), 81–90.

    Google Scholar 

  • Ryan, M. K., Haslam, S. A., Hersby, M. D., & Bongiorno, R. (2011). Think crisis-think female: The glass cliff and contextual variation in the think manager-think male stereotype. Journal of Applied Psychology, 96(3), 470.

    Google Scholar 

  • Ryan, M. K., Haslam, S. A., & Kulich, C. (2010). Politics and the glass cliff: Evidence that women are preferentially selected to contest hard-to-win seats. Psychology of Women Quarterly, 34(1), 56–64.

    Google Scholar 

  • Sanbonmatsu, K., & Dolan, K. (2009). Do Gender stereotpes transcend party? Political Research Quarterly, 62(3), 485–494.

    Google Scholar 

  • Schaffner, B. F., Macwilliams, M. C., & Nteta, T. (2018). Understanding white polarization in the 2016 vote for president: The sobering role of racism and sexism. Political Science Quarterly. https://doi.org/10.1002/polq.12737.

    Article  Google Scholar 

  • Simas, E. N., & Bumgardner, M. (2017). Modern sexism and the 2012 U.S. presidential election: Reassessing the casualties of the war on women. Politics and Gender, 13(3), 359–378.

    Google Scholar 

  • Swim, J. K., Aikin, K. J., Hall, W. S., & Hunter, B. A. (1995). Sexism and racism: Old-fashioned and modern prejudices. Journal of Personality and Social Psychology, 68(2), 199.

    Google Scholar 

  • Trump, D. (2016). Full text: Donald Trump campaign speech in Wisconsin.

  • Valentino, N. A., Wayne, C., & Oceno, M. (2018). Mobilizing sexism the interaction of emotion and gender attitudes in the 2016 us presidential election. Public Opinion Quarterly, 82(S1), 799–821.

    Google Scholar 

  • Weinschenk, A. C., & Dawes, C. T. (2019). Moral foundations, system justification, and support for Trump in the 2016 presidential election. The Forum, 17, 195–208.

    Google Scholar 

  • Womick, J., et al. (2019). Group-based dominance and authoritarian aggression predict support for Donald Trump in the 2016 U.S. presidential election. Social Psychological and Personality Science, 10(5), 643–652.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Political Science, University of Houston, 3551 Cullen Boulevard, Room 447, Philip Guthrie Hoffman Hall, Houston, TX, 77204-3011, USA

    Elizabeth N. Simas

Authors
  1. Elizabeth N. Simas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Elizabeth N. Simas.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 38 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Simas, E.N. But Can She Make America Great Again? Threat, Stability, and Support for Female Candidates in the United States. Polit Behav 44, 1–21 (2022). https://doi.org/10.1007/s11109-020-09607-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11109-020-09607-4

Keywords

Search

Navigation