‘Whiny, Fake, and I Don't Like Her Hair’: Gendered Assessments of Mayoral Candidates
Bibliographic record
Abstract
Municipal mayoral elections present a compelling puzzle: what happens when gendered stereotypes about level of government conflict with those about type of office? Although local politics is viewed as communal and more feminine, the mayoral office is a prominent, prestigious position of political leadership that voters may perceive as more masculine. We intervene by analyzing open-ended comments about 32 mayoral candidates from a survey of 14,438 municipal electors in eight Canadian cities. We argue gendered trait and issue stereotypes are embedded in voters’ assessments of mayoral candidates. We find no evidence that female candidates benefit from their perceived competence in local policy issues, and they experience backlash when they display the traits typically associated with strong leaders. We conclude that, even at the level of government frequently thought of as more open to women, female mayoral candidates are disadvantaged by an enduring association between masculinity and political leadership.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.245 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".