La santé mentale au travail : pour une compréhension de cet enjeu de santé publique
Bibliographic record
Abstract
The Western countries, mental health problems are increasing and represent one of the major causes of morbidity of the population with an annual prevalence varying from 15 to 25%. Consequences of this morbidity are more importantly felt on the working capacity of individuals. Several elements linked particularly to the evolution of the organization and working conditions in the course of the last years incriminate the workplace in explaining the origin of this new "epidemic". If there is a relative unanimity on the importance of mental health problems at work, it is not the case with the understanding of the origin of these problems and, consequently, of the strategies to put in place to counter them. Of the entire studies that have attempted to explain this phenomenon, three approaches are considered: the causalist approach, the cognitivist approach and finally, the psychodynamic approach. Even if the cognitivist approach allows the understand why some stress factors identified by the causalist approach can be pathogenic, it appears a bit reductionist by linking mental health problems at work with the failure of people's efforts of adaptation. Contrarily on the cognitivist interpretation and to individual actions which brings us to the approach to stress, the psychodynamic of work leads to a questioning of the intelligibility of the organizational origin of mental health problems at work, by analyzing the dynamic and evolutive interface between the objectives pursued by the individual, the organization and the working group.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".