Les femmes nommées ministres au Canada pendant la période 1921-2007 : la loi de la disparité progressive est-elle dépassée?
Bibliographic record
Abstract
Ce texte examine la participation des femmes aux cabinets canadiens, et ce, à la lumière de la loi de la disparité progressive. Trois hypothèses l’ont inspiré : 1) la proportion de femmes nommées ministres est plus élevée que la proportion de femmes élues députées; 2) la proportion de femmes au Cabinet reflète la proportion de députées au sein du caucus parlementaire du parti qui forme le gouvernement; 3) les femmes nommées ministres sont cantonnées dans les secteurs traditionnellement considérés comme féminins et au bas de la hiérarchie exécutive. Ces hypothèses ont été vérifiées auprès des 286 femmes nommées ministres dans un cabinet fédéral ou provincial au Canada de 1921 à 2007. Il ressort de l’analyse que la loi de la disparité progressive offre un potentiel heuristique mitigé pour expliquer la participation des femmes aux cabinets canadiens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 source (direct Gemma or distilled Codex), 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".