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Race, Gender, and Nascent Political Ambition

Published online by Cambridge University Press:  18 December 2025

Andrea Junqueira
Affiliation:
Department of Government, Law & Policy, Arkansas State University, Jonesboro, AR, USA
Diana Z. O’Brien*
Affiliation:
Department of Political Science, Washington University in St. Louis, Saint Louis, MO, USA
Matthew Hayes
Affiliation:
Department of Political Science, Washington University in St. Louis, Saint Louis, MO, USA
Jongwoo Jeong
Affiliation:
Department of Political Science, Georgia State University, Atlanta, GA, USA
Brian Crisp
Affiliation:
Department of Political Science, Washington University in St. Louis, Saint Louis, MO, USA
Matthew Gabel
Affiliation:
Department of Political Science, Washington University in St. Louis, Saint Louis, MO, USA
*
Corresponding author: Diana Z. O’Brien; Email: dzobrien@wustl.edu
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Abstract

How do race and gender together shape Americans’ political ambition? Using original survey data with over-samples of black and Hispanic respondents, we analyze citizens’ nascent ambition for eight political offices across racial/ethnic groups and gender. We reveal that the primary gap in nascent political ambition is not between men and women but between white men and the majority of the polity. There is no consistent gender gap in ambition among black or Hispanic respondents, nor between black and Hispanic men and white women. The gap between white men and other respondents is most pronounced for local offices, which mark both the starting point and final stage of many political careers. Our findings further indicate that while white men are particularly responsive to encouragement from non-political sources, ambition gaps narrow among respondents encouraged by political actors. Together, these insights help explain the persistence of white men’s overrepresentation in US politics.

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Type
Letter
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. Effect of race–gender on nascent political ambition, as compared to white men respondents.Note: The top panel plots the average marginal effects, with ‘white men’ as the reference category. The bottom panel plots the predicted probabilities. Predictions were generated by setting all remaining variables to their means (for continuous variables) or their modes (for categorical variables). Estimates were constructed using ninety-five per cent confidence intervals and robust standard errors.

Figure 1

Figure 2. Effect of gender and race on nascent political ambition by office type, as compared to white men respondents.Note: The top plot presents the average marginal effects, with ‘white men’ as the reference category. The bottom panel plots the predicted probabilities that respondents from each group will report having considered running for a given office. Predictions were generated by setting all remaining variables to their means (for continuous variables) or their modes (for categorical variables). Estimates were constructed using ninety-five per cent confidence intervals and standard errors clustered by the respondent.

Figure 2

Figure 3. Effect of encouragement by gender and race.Note: The top panel displays the average marginal effects with ‘white men’ as the reference category. The bottom panel plots the predicted probabilities. Predictions were generated by setting all remaining variables to their means (for continuous variables) or their modes (for categorical variables). Due to the small number of black women who reported receiving encouragement exclusively from a political source, our prediction approaches zero with narrow standard errors. Estimates were constructed using ninety-five per cent confidence intervals and robust standard errors.

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