mardi 06 mai 2025
11:00 - 12:00
B18.005 (Brig Campus) and online

What causes the beauty premium in elections? Two decades of research show that more physically attractive candidates get more votes. Most studies assume a direct link between voter evaluations of candidate appearance and electoral support, even though many voters may not have knowledge of how a candidate may look. We argue that the causal story is more complicated: good-looking candidates may get more votes in part because they raise more money and are nominated to more winnable districts by party elites. To evaluate our argument, we evaluate the facial attractiveness of 1,200 candidates for the 2019 Canadian federal election using pretrained image classification models based on convolutional neural networks (Lindholm et al. 2024). Combined with existing datasets on candidate characteristics (e.g., gender, party affiliation, vote share, competitiveness of the election) and donations (number and amount of received donations as well as gender of each donor), this measure allows us to model both the direct effect of attractiveness and of the proposed mediators on political donations and eventual vote share. Data on donor gender also allows us to test expectations for gendered responses to candidate appearance. We will also explore the relationship between facial dominance and trustworthiness of candidates by political party and total donations. The attractiveness premium is often taken as evidence of voter incompetence; assessing alternative explanations for this relationship can help determine whether that interpretation is warranted and provide evidence toward potential biases in how elites nominate and support candidates.

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Speaker

Professor Friesen is interested in how social identities and individual dispositions interact with social and political contexts, particularly as it pertains to resilience and efficacy. Her methodological approaches draw from behaviour genetics, psychophysiology, personality psychology, experimental design, and other social and life science methods.