Name Heuristics: Race and Gender Stereotypes in Non-Partisan Elections

• In Event: Unmasking Race in Elections

Abstract

Using an original dataset of over 20,000 non-partisan campaigns in California between 2011 and 2018 I show that voters rely on the candidates name to vote along gendered and race conscious lines. Without the most effective and important voting heuristic, partisan identification, voting behavior is guided by gender and racial stereotypes. This is true for both conservative counties where the bias is strongest against racial minorities, as well as liberal counties where the bias is in favor of females. This paper contributes to the existing literature through analysis by the types of office sought. Although women did worse across all categories as the electoral area became more conservative, this was especially true in core government positions such as mayor, city council, treasurer, and comptroller. Women performed better when seeking positions in the domain of education or services (parks and recreation, transit, etc.). This pattern is even more dramatic with Hispanic candidates, who generally did worse in more conservative districts; the exception being service positions, where there was no noticeable drop offs. Against expectations, I found that Asian Americans did poorly seeking offices related to education regardless of the political ideology of the electoral district.

Author

• Bryan FitzGerald