Skip to main content

Gender Stereotypes, Information Search, and Voting Behavior in Political Campaigns

Abstract

It is still unclear exactly how gender influences vote choice. Using an information processing perspective, we argue that instead of directly influencing vote choice, candidate gender guides the amounts and types of information that voters search for during a campaign, and that effects of gender on vote choice ultimately come from differences in information search influenced by candidate gender. Using two unique experimental datasets, we test the effects of candidate gender on vote choice and information search. We find that subjects change their search based on a candidate’s gender, seeking out more competence-related information about female candidates than they do for male candidates, as well as more information related to “compassion issues.” We also find that evaluations of candidates’ traits and issue positions are important predictors of subjects’ vote choice.

This is a preview of subscription content, access via your institution.

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

Notes

  1. See http://www.processtracing.org for the Dynamic Process Tracing Environment (DPTE) software and user guide. Any researcher may request access to the system for research purposes by clicking on the appropriate link on the website. Funding for DPTE and some of the research reported here was provided by support from the National Science Foundation and the University of Iowa.

  2. See Figure 1 in the Online Appendix.

  3. In Study 1, participants could also learn information from campaign television ads which periodically took over the computer screen, interrupting the information search process. These 20 s ads were typical of presidential campaign advertisements, except that for the most part they were positive in nature, highlighting one particular issue for each candidate. There was nothing in the ads that could not be learned by clicking on the scrolling boxes and reading the resulting detailed positions. Video ads were not used in Study 2.

  4. Extensive details on the study are available in Lau and Redlawsk 2006. The number of participants was 194 for Experiment 1, 97 for Experiment 2, and 107 for Experiment 3. Participants, while not a random sample, generally represented the demographics of the area from which they were recruited.

  5. There were four possible candidate “personas” in each party’s primary. Among the Democrats, there was an extremely liberal candidate, a “mainstream” liberal candidate, a somewhat conservative candidate, and a “mixed” candidate who took both conservative and liberal positions, but averaged right down the center. Likewise, Republican primary voters could choose among a mixed-ideology Republican candidate, a relatively liberal Republican candidate, a mainstream (conservative) Republican and an extremely conservative Republican. In each party, the “mixed-ideology” candidate and the “mainstream” liberal or conservative candidate were designated for the gender manipulation; all other candidates were always male. See Figure 2 in the Online Appendix.

  6. Participants chose the party in which they wished to vote in the primary; when we refer to in-party this is the party they voted in, the out-party is the other party. Where appropriate in the analyses below we control for the number of primary in-party candidates.

  7. In four additional cases there were female candidates in both parties. Because we are interested in comparing male candidates to female candidates, we dropped those cases from the analysis.

  8. These include exposure to either two or three campaigns simultaneously, as well as variation in the office at the “top of the ticket” between the Presidency and Governor. Participants always saw a race for the House of Representatives, while half saw a presidential race and half saw a gubernatorial race. Half of the sample also saw a Senate race, while the other half did not. There were a total of 279 participants overall, but since we manipulated gender only in the presidential campaign our effective sample is the 132 participants who saw that campaign. The other unrelated manipulations affected the information environment during the campaigns. Half of participants saw campaigns with a “realistic” Distribution of information, where there was more information available for the presidential candidates than for the House candidates. Others experienced campaigns that had “equal resources,” so there were equal numbers of information boxes no matter the level of the office sought. Finally, the media attribution for some information was varied so that some participants saw certain information from conservative outlets, others saw information from liberal outlets, and another third saw no attribution. All of these treatments were randomly assigned and are controlled for in our analyses.

  9. Unlike Study 1, candidates did not vary by ideology—the Democratic candidate always had “mainstream” liberal Democratic issue stances, while the Republican always had “mainstream” conservative Republican positions.

  10. Participants who identified as independent were asked which party they felt closer to, and were placed in the appropriate group. Those who could not choose a party were dropped from these analyses.

  11. Pictures of the candidates in the race are available in the online appendix.

  12. Because the vast majority of the information voters could view was text, and the length of each item varied, the time it took participants to read items would also influence information search. Thus we control for the number of words in each item and the reading ability of the voter. Reading ability was measured as the time it took each subject to read the instructions and scenario presented before the experiment began, which was automatically calculated by the computer. Full models are available from the authors upon request.

  13. We examined whether there were partisan differences between voters in information search for male and female candidates. The results (not shown) also fit the voting model, with partisans of both parties equally likely to focus on female candidates.

  14. As with the primary election the general election model controls for total information search, the number of words in each item and participants’ reading ability, as well as for the vote preference.

  15. Again, we only present figures for statistically significant results. The results for total search and trait-based search can be found in Figure 7 in the Online Appendix.

References

  • Alexander, D., & Andersen, K. (1993). Gender as a factor in the attribution of leadership traits. Political Research Quarterly, 46(3), 527–545.

    Article  Google Scholar 

  • Atkeson, L. R. (2003). Not all cues are created equal: The conditional impact of female candidates on political engagement. Journal of Politics, 65, 1040–1061.

    Article  Google Scholar 

  • Burrell, B. C. (1994). A woman’s place is in the house: Campaigning for congress in the feminist era. Ann Arbor: University of Michigan Press.

    Google Scholar 

  • Bystrom, D. (2010). 18 million cracks in the glass ceiling: The rise and fall of Hillary Rodham Clinton’s Presidential bid. In R. Murray (Ed.), Cracking the highest glass ceiling: A global comparison of women’s campaigns for executive office (pp. 69–90). Santa Barbara, CA: Praeger.

    Google Scholar 

  • Campbell, A., Converse, P., Miller, W. E., & Stokes, D. E. (1960). The American voter. New York: John Wiley and Sons.

    Google Scholar 

  • Carroll, S. J. (2009). Reflections on gender and Hillary Clinton’s presidential campaign: The good, the bad, and the misogynic. Politics and Gender, 5(1), 1–20.

    Article  Google Scholar 

  • Carroll, S. J., & Dittmar, K. (2010). The 2008 candidates of Hillary Clinton and Sarah Palin: Cracking the “highest, hardest glass ceiling”. In S. J. Carroll & R. L. Fox (Eds.), Gender and elections: Shaping the future of American politics (2nd ed., pp. 117–143). New York: Cambridge University Press.

    Google Scholar 

  • Cook, E. A. (1994). Voter responses to women candidates. In E. A. Cook, T. Sue, & W. Clyde (Eds.), The year of the women: Myths and realities. Boulder, CO: Westview.

    Google Scholar 

  • Darcy, R., Welch, S., & Clark, J. (1994). Women, elections, and representation (2nd ed.). Lincoln: University of Nebraska Press.

  • Dolan, K. (1998). Voting for women in the “year of the woman”. American Journal of Political Science, 42(1), 272–293.

    Article  Google Scholar 

  • Dolan, K. (2004). Voting for women: How the public evaluates women candidates. Boulder, CO: Westview Press.

    Google Scholar 

  • Fox, R. L. (2010). Congressional elections: Women’s candidacies and the road to gender parity. In S. J. Carroll & R. L. Fox (Eds.), Gender and elections: Shaping the future of American politics (2nd ed., pp. 187–209). New York: Cambridge University Press.

    Google Scholar 

  • Huang, L.-N. (2000). Examining candidate information search processes: The impact of processing goals and sophistication. Journal of Communication, 50(Winter), 93–114.

    Article  Google Scholar 

  • Huang, L.-N., & Price, V. (2001). Motivations, goals, information search, and memory about political candidates. Political Psychology, 22, 665–692.

    Article  Google Scholar 

  • Huddy, L., & Terkildsen, N. (1993). The consequences of gender stereotypes for women candidates at different levels and types of office. Political Research Quarterly, 46(3), 503–525.

    Article  Google Scholar 

  • Kahn, K. F. (1992). Does being male help? An investigation of the effects of candidate gender and campaign coverage on evaluations of U.S. Senate candidates. Journal of Politics, 54(May), 497–517.

    Article  Google Scholar 

  • Kahn, K. F. (1994). Does gender make a difference? An experimental examination of sex stereotypes and press patterns in statewide campaigns. American Journal of Political Science, 38(1), 162–195.

    Article  Google Scholar 

  • Kahn, K. F. (1996). The political consequences of being a woman. New York: Columbia University Press.

  • Koch, J. (1999). Candidate gender and assessments of senate candidates. Social Science Quarterly, 80, 84–96.

    Google Scholar 

  • Koch, J. (2000). Do citizens apply gender stereotypes to infer candidates’ ideological orientations? The Journal of Politics, 62(2), 414–429.

    Article  Google Scholar 

  • Lau, R. R., & Redlawsk, D. P. (1997). Voting correctly. American Political Science Review, 91(September), 585–599.

    Article  Google Scholar 

  • Lau, R. R., & Redlawsk, D. P. (2001). Advantages and disadvantages of cognitive heuristics in political decision making. American Journal of Political Science, 45(October), 951–971.

    Article  Google Scholar 

  • Lau, R. R., & Redlawsk, D. P. (2006). How voters decide: Information processing during an election campaign. New York: Cambridge University Press.

    Book  Google Scholar 

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

    Article  Google Scholar 

  • Lawless, J. L., & Fox, R. L. (2005). It takes a candidate: Why women don’t run for office. New York: Cambridge University Press.

    Google Scholar 

  • Leeper, M. S. (1991). The impact of prejudice on female candidates: An experimental look at voter inference. American Politics Quarterly, 19(2), 248–261.

    Article  Google Scholar 

  • Lodge, M., McGraw, K. M., & Stroh, P. (1989). An impression driven model of candidate evaluation. American Political Science Review, 83(June), 399–419.

    Article  Google Scholar 

  • McDermott, M. L. (1998). Race and gender cues in low-information elections. Political Research Quarterly, 51(4), 895–918.

    Article  Google Scholar 

  • Plutzer, E., & Zipp, J. F. (1996). Identity politics, partisanship, and voting for women candidates. Public Opinion Quarterly, 60, 30–57.

    Article  Google Scholar 

  • Redlawsk, D. P., & Lau, R. R. (2013). Behavioral decision theory. In L. Huddy & J. Levy (Eds.), Oxford handbook of political psychology. Oxford: Oxford University Press.

    Google Scholar 

  • Riggle, E. D. B., & Johnson, M. M. S. (1996). Age differences in political decision making: Strategies for evaluating political candidates. Political Behavior, 18, 99–118.

    Article  Google Scholar 

  • Rosenwasser, S. M., & Seale, J. (1988). Attitudes toward a hypothetical male or female presidential candidate—A research note. Political Psychology, 9(4), 591–598.

    Article  Google Scholar 

  • Sanbonmatsu, K. (2002). Gender stereotypes and vote choice. American Journal of Political Science, 46(March), 20–34.

    Article  Google Scholar 

  • Sanbonmatsu, K., & Dolan, K. (2008). Do gender stereotypes transcend party? Political Research Quarterly, 61(1), 79–89.

    Article  Google Scholar 

  • Schneider, M., & Angela, B. (2011) Measuring stereotypes of female politicians. Paper presented at the annual meeting of the American Political Science Association.

  • Seltzer, R., Newman, J., & Leighton, M. V. (1997). Sex as a political variable: Women as candidates and voters in U.S. elections. Boulder: Lynne Rienner.

    Google Scholar 

  • Smith, J. L., Paul, D., & Paul, R. (2007). No place for a woman: Evidence for gender bias in evaluations of presidential candidates. Basic and Applied Social Psychology, 29(3), 225–233.

    Article  Google Scholar 

  • Stokes-Brown, A. K., & Neal, M. O. (2008). Give ‘em something to talk about: The influence of female candidates’ campaign issues on political proselytizing. Politics and Policy, 36, 32–59.

    Article  Google Scholar 

  • Woods, H. (2000). Stepping up to power: The political journey of American women. Boulder: Westview Press.

    Google Scholar 

  • Zipp, J. F., & Plutzer, E. (1985). Gender differences in voting for female candidates: Evidence from the 1982 election. Public Opinion Quarterly, 49, 179–197.

    Article  Google Scholar 

Download references

Acknowledgments

The authors gratefully acknowledge National Science Foundation grants in partial support of these studies including SBR-9411162, supporting data collection for Study 1, and SES-0647738 and SES-1022551, supporting the further development of the Dynamic Process Tracing Environment software. Thanks also to David Andersen and Richard Lau for their help with the design and programming of Study 2, as well as Tracy Osborn, Caroline Tolbert, and Jason Windett who read early versions of this article and provided helpful comments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tessa M. Ditonto.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 2551 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Ditonto, T.M., Hamilton, A.J. & Redlawsk, D.P. Gender Stereotypes, Information Search, and Voting Behavior in Political Campaigns. Polit Behav 36, 335–358 (2014). https://doi.org/10.1007/s11109-013-9232-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11109-013-9232-6

Keywords

  • Gender
  • Stereotypes
  • Vote choice
  • Information search
  • Decision-making