Researchcomputer visionpolitical behaviorgender bias
Candidate Smiles Significantly Affect Electoral Outcomes
7.6
A recent study analyzing 9,000 French local election manifestos (2022 and 2024) and a 1,000-person online experiment used AI to detect candidate smiles and measure voter responses. It finds non-smiling female candidates lose roughly two to three percentage points relative to non-smiling men, while smiling adds value for men. The results indicate asymmetric gendered penalties with implications for campaign imagery strategies.
Key Points
- 1Finds non-smiling female candidates lose about two to three percentage points versus non-smiling male counterparts.
- 2Highlights gender stereotypes create warmth-versus-authority tension, causing asymmetric electoral penalties for women.
- 3Advises campaigns to manage female candidate imagery carefully; non-smiling risks measurable vote losses.
Scoring Rationale
Provides strong empirical evidence quantifying gendered smile penalties, but remains preliminary and focused on French elections.
Sources
Public references used for this report.
Practice interview problems based on real data
1,625 SQL & Python problems across 15 industry datasets — the exact type of data you work with.
Try 250 free problems
