S’attaquer à la sous-scolarisation des hommes, sans nuire au succès des femmes
Bibliographic record
Abstract
→ Book launch on March 28, 2023 at CIRANO In terms of schooling, major upheavals have occurred in Quebec over the past few decades. There has been a huge catch-up of women in university attainment, particularly in certain disciplines such as education, health, and social and life sciences, but much less in STEM. Is this a problem? Not really. The problem is with the men. In La sous-scolarisation des hommes et le choix de profession des femmes, published by the Presses de l'Université de Montréal, the authors debunk several myths and take a critical, reflexive and well-documented look at initiatives aimed at influencing women's career choices and instead shine a spotlight on the economic and social issues surrounding the lack of gender diversity in key sectors of the economy. → Lancement du livre le 28 mars 2023 au CIRANO En matière de scolarisation, d’importants bouleversements se sont produits au cours des dernières décennies au Québec. On a assisté à un rattrapage énorme des femmes sur le plan des études universitaires, et en particulier dans certaines disciplines comme l’éducation, la santé et les sciences sociales et sciences de la vie, mais beaucoup moins dans les STIM. Est-ce un problème ? Pas vraiment. Le problème, c’est du côté des hommes. Dans La sous-scolarisation des hommes et le choix de profession des femmes publié aux Presses de l’Université de Montréal, les auteurs déboulonnent plusieurs mythes et posent un regard critique, réflexif et largement documenté sur les initiatives visant à influencer les choix de carrière des femmes et braquent plutôt les projecteurs sur les enjeux économiques et sociaux du manque de mixité dans des secteurs clés de l’économie.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.075 | 0.017 |
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".