La formation des femmes en France : évolution et paradoxe d’une situation qui perdure
Bibliographic record
Abstract
En France, les jeunes femmes affichent un taux de réussite supérieur à celui de leurs homologues masculins à tous les niveaux du système éducatif. Malgré cette supériorité, peu de femmes se spécialisent dans des matières scientifiques pour choisir les disciplines et les professions conformes aux rôles traditionnels déterminés par leur genre. Par ailleurs, encore peu de femmes sont titulaires de diplômes avancés, ce qui les empêche d’atteindre un niveau de réussite professionnelle correspondant à leurs capacités. Le ministère français de l’Éducation nationale a pris des mesures afin de modifier les mentalités et d’offrir les mêmes débouchés aux hommes et aux femmes, mais les progrès demeurent lents.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".