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Differences in Appearance-Based Trait Inferences for Male and Female Political Candidates

Bibliographic Data

ID6409702
AuthorsTessa Ditonto (0000-0001-6503-6651, Iowa State University, corresponding author), Kyle Mattes (0000-0002-9665-8776, Florida International University)
Year2018
Volume39
Issue4
Pages430-450
Publication date2018-10-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueWomen & Politics (JOURNAL)
Journal identifiersISSN: 0195-7732 • E-ISSN: 1540-9473
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/1554477x.2018.1506206
OpenAlexW2899993548
LanguageEN
Citations received8
References cited76

Studies show that automatic trait inferences can predict outcomes of actual elections, but these studies generally include male candidates only. Substantial evidence also shows that female candidates are subject to gender-based stereotypes, which can lead to differences in how men and women candidates are evaluated. This article combines these two literatures to compare the effects of competence, threat, and attractiveness inferences in elections that include women. We use experimental data in which candidate pairs from state and local US elections were judged on these three traits and examine whether those ratings are predictive of election outcomes. We find that although competence matters most for elections involving only men, attractiveness predicts winners in women-only elections. In mixed-gender races, competence inferences predict success when the female candidate is perceived as more competent than the male candidate. Finally, unlike men, women benefit from being perceived as physically threatening in mixed-gender races

Attractiveness · Competence (human resources · Developmental psychology · Political science · Politics · Trait · Computer Science · Evolutionary Psychology and Human Behavior · Gender Roles and Identity Studies · Psychology · Social and Intergroup Psychology · Social Psychology

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Unique citing works8
Citations per year1,14
Citation span2019 - 2025 (7)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 8

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