Le gender mainstreaming, entre objectivation institutionnelle et apprentissage de l’égalité1
Bibliographic record
Abstract
L’article analyse les modalités concrètes de la mise en oeuvre du gender mainstreaming dans les politiques d’emploi à Berlin et en Île-de-France au cours des années 2000. Il analyse les logiques de fonctionnement et les usages des deux principaux instruments qui opérationnalisent cette approche de l’égalité entre les sexes : les postes de promotion de l’égalité et les formations à l’égalité au sein des services publics de l’emploi français et allemand. Si l’introduction de ces instruments légitime la prise en compte de l’objectif d’égalité au sein des services publics de l’emploi et marque un changement important dans le diagnostic porté sur les causes des inégalités entre les sexes dans l’emploi, leur réappropriation par la majorité des acteurs de ces politiques reste limitée.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".