Accompagnement et injonctions sociales dans les tribunaux de santé mentale
Bibliographic record
Abstract
Depuis les années 90, les tribunaux spécialisés ont émergé dans le paysage judiciaire. Cet article s’intéresse particulièrement aux tribunaux de santé mentale, conceptualisés comme étant le fruit d’une hybridation entre le droit et la psychiatrie. S’inscrivant dans le cadre d’une thèse, cet article exposera la manière dont les discours concernant la santé mentale et la normativité sociale sont intégrés dans ce type de tribunal et influencent leurs pratiques. Plus précisément, il sera illustré que les injonctions liées au récit biographique, à la responsabilité et à l’activation sont déterminantes dans le parcours des personnes interpellées par ce tribunal. Le regard transversal permettra d’éclairer la tension entre vulnérabilité sociale et régulation pénale des problèmes sociaux complexes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".