Le lien entre la santé mentale et la satisfaction des besoins d'autonomie, de compétence et d'affiliation sociale
Bibliographic record
Abstract
Résumé Les problèmes de santé mentale au travail augmentent en variété, en gravité et en fréquence, entraînant des coûts financiers, commerciaux et humains importants pour les organisations. Cet article vise à présenter aux cadres trois grandes pistes d’intervention pour optimiser la santé mentale des employés. Ces cibles d’action reposent sur trois besoins psychologiques essentiels à l’être humain, soit les besoins d’autonomie, de compétence et d’affiliation sociale. La non-satisfaction de ces besoins, qui sont trop souvent frustrés, voire ignorés, est à l’origine de nombreux cas de détresse psychologique. Dans cet article, nous proposons des moyens de faire en sorte que ces besoins soient comblés chez les employés, maximisant ainsi les chances que ces derniers aient une bonne santé mentale, avec tous les bénéfices que cela apporte tant aux employés qu’aux employeurs. Fonctions : GRH, management Industrie : toutes
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".