La difficile reconnaissance du caractère professionnel des atteintes à la santé mentale
Bibliographic record
Abstract
Des évolutions récentes dans la prise en compte des risques psychosociaux ainsi que dans la réglementation, la jurisprudence et les pratiques administratives, ont permis une amélioration de la reconnaissance en accidents du travail ou en maladies professionnelles des atteintes à la santé mentale. Cependant, les démarches pour obtenir cette reconnaissance demeurent difficiles pour les salariés concernés, du fait de la complexité des procédures, mais aussi de l’écart entre le rôle prescrit des acteurs (employeur, médecin du travail, etc.) et leur conduite réelle, et enfin à cause du retentissement possible de la démarche sur la situation de la personne. L’accompagnement par des acteurs aux compétences complémentaires (médecin, psychologue, juriste) apparaît pertinent pour éviter les impasses.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".