Les femmes dans les métiers non-traditionnels : le général, le particulier et l'ergonomie
Bibliographic record
Abstract
Résumé Wisner a mis l’accent sur la diversité des êtres humains et sur la nécessité d’adapter le travail à « l’homme ». Il a aussi prôné la nécessité d’élargir les cadres d’analyse pour tenir compte d’un plus grand ensemble d’éléments de la demande sociale. Les études ergonomiques visant le maintien des femmes dans les milieux non-traditionnels ( mntf ) peuvent ainsi être interrogées à la lumière des apports de Wisner. 1) Est-il suffisant de considérer l’adaptation du travail à chaque femme ou devons-nous nous pencher sur cette population en tant que groupe ? 2) Est-ce à l’ergonome d’incorporer les aspects sociaux du travail dans son intervention en mntf ? 3) L’étude ergonomique des Mntf respecte-t-elle les critères de recherche scientifique ?
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".