Gender and Political Party Leadership in Canada
Why this work is in the frame
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Bibliographic record
Abstract
In this article, we compare the experiences of male and female party leaders at the provincial and federal levels in Canada between 1980 and 2005 and test several hypotheses regarding gender and party leadership. The Canadian case provides an excellent case study given the relatively large number of women (21 in total) who held the position of party leader during the time period in question. The case study reveals that major parties are less likely to elect women as their leaders, while parties on the ideological left are more likely than other parties to select women. The leadership races won by women are as competitive, if not more so, than those won by men, although the mandate secured by women leaders is less overwhelming. Not surprisingly, then, men are found to enjoy longer tenures as leaders than women, and, moreover, to enjoy greater electoral success.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it