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 ?
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 | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".