Popular accounts of the 2016 presidential election attribute Donald Trump’s victory to the mobilization of angry white men seeking to restore traditional values and social roles. Whereas a majority of Trump voters were male, more than 40% of women who went to the polls on Election Day also supported him. This analysis explores the motivations of these women, asking how partisanship, demographics, and beliefs motivated their vote choice. We found that, although party affiliation was an important predictor of both women’s and men’s vote choice, sexism and racial resentment had a greater influence on voters of both genders. Moreover, the influence of these biases was similar for women and men.
Objective. Palmer and Simon's (2008) "women-friendly" district index has proven a useful theoretical and empirical construct for researchers studying congressional elections. In one parsimonious measure, the authors capture 12 factors predicting women's election to the House of Representatives. The construct's utility in other political contexts, however, has not yet been tested. Methods. We test the women-friendliness index using a new data set on state legislative elections. Results. We find that the women-friendly district index is useful for predicting the election of women in state legislatures. The index's predictive power is robust to institutional variations and surpasses other contextual indicators, such as political culture. Conclusions. Our analysis suggests that "women friendliness" is a useful empirical concept with application in multiple political contexts.
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