Gender, Race and Political Ambition: The Case of Ontario School Board Elections
Bibliographic record
Abstract
Abstract The political underrepresentation of women and racial minorities in Canadian politics is well documented. One political arena that has yet to be examined in this respect, however, is school boards. Using data from a candidate survey conducted during the course of the 2018 Ontario school board elections, as well as demographic data collected on the entire population of school board candidates, we explore the unique characteristics of school board elections. The research note begins by describing the gender and racial composition of candidates and trustees in Canada's most populous province. It then considers the ways in which school board elections may serve as a launchpad to higher office for either of these two traditionally underrepresented groups, as we explore the features of progressive political ambition, recruitment into school board campaigns and the relative electoral success of racialized candidates and women in this local office. While women do very well in school board elections, they are significantly less likely than their male counterparts to have the desire to move up to provincial or federal politics. Meanwhile, racialized candidates contest school board election in significant numbers and report similar levels of progressive ambition relative to their white counterparts, but they fare exceptionally poorly in school board elections.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".