Gender-Trait and Ethnic Biases in Russian Regions: Ethnic Integration, Regional Economies, and Women in Local Politics

Under what conditions are voters likely to invoke gender-trait stereotypes and ethnic biases when they evaluate the performance of local political leaders? We test arguments from role congruity and social identity theories and employ intersectional analysis to explore voter reliance on gender-trait...

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Bibliographic Details
Published in:Politics & gender 2021-12, Vol.17 (4), p.720-745
Main Authors: Avdeyeva, Olga A., Matland, Richard E.
Format: Article
Language:English
Subjects:
Bias
Economic concentration
Economic integration
Ethnic identity
Ethnicity
Gender
Intersectionality
Labor market
Leadership
Local politics
Minority & ethnic groups
Minority groups
Policy making
Political leadership
Regions
Research Article
Roles
Social groups
Social identity
Stereotypes
Voters
Women
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Summary:Under what conditions are voters likely to invoke gender-trait stereotypes and ethnic biases when they evaluate the performance of local political leaders? We test arguments from role congruity and social identity theories and employ intersectional analysis to explore voter reliance on gender-trait stereotypes and ethnic biases across four diverse Russian regions. We find that the structure of the regional economy matters for the reduction of gender-trait stereotypes, while spatial and labor market integration matters for the dissipation of ethnic favoritism in leader evaluation. Our findings have important implications for policy makers aiming to reduce political biases in diverse contexts. On the one hand, we encourage scholars to pay careful attention to stereotypes of underrepresented social groups and evaluate how they can translate into understanding the traits associated with good leadership. On the other hand, we demonstrate that the roots of social biases stem from complex structural phenomena, such as limited labor opportunities for women and minorities, and thus require transformative political and economic changes.
ISSN:1743-923X
1743-9248
DOI:10.1017/S1743923X2000001X