Dimensions prioritaires à considérer afin d’améliorer le processus de rétablissement des patients souffrant de troubles mentaux graves associés à une problématique de violence ou de comportements antisociaux
Bibliographic record
Abstract
L’amélioration de la prévention et des traitements des comportements antisociaux et de violence chez les personnes atteintes de troubles mentaux graves est une tâche complexe. De multiples interventions à différents niveaux doivent être instaurées. Certaines dimensions sont à encourager pour améliorer le succès des interventions et appuyer le processus de rétablissement des personnes souffrant de troubles mentaux graves. Le but de cet article sera de démontrer que 2 dimensions sont à prioriser : 1- diminuer la discrimination ou la stigmatisation et 2- favoriser l’intégration des services de santé mentale, d’alcoolisme et de toxicomanie et de justice offerts aux personnes souffrant de troubles mentaux graves afin d’assurer une cohérence et une continuité des soins. Ces composantes prioritaires seront discutées en évaluant les modèles en place et leur pertinence quant à la mise en oeuvre d’actions ciblées et efficaces.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".