Les Tribunaux de santé mentale : déjudiciarisation et jurisprudence thérapeutique
Bibliographic record
Abstract
In Québec, as elsewhere in North America, psychiatric deinstitutionalization, lack of community mental health resources as well as legislative changes to civil and criminal codes have led to an increased probability that individuals with a mental illness come into contact with the criminal justice system. Based on the principle of therapeutic jurisprudence, mental health courts constitute emerging diversion programs, taking place within the court, implemented to offer an alternative to incarceration for individuals with a mental illness. This article offers a critical synthesis of the scientific literature on the topic. The authors first present the context in which mental health courts were developed ; describe their objectives and functioning ; and introduce the Montreal Mental Health Court pilot project, renamed PAJ-SM (Plan d'Accompagnement Justice et Santé) the first of its kind in Québec. The paper examines the research on mental health courts and tackles some of the stakes of diversion programs. The challenges and limits inherent to specialized courts are discussed as well as methodological obstacles related to the study of these complex intervention programs. The authors conclude that mental health courts offer promising intervention venues, but that they do not constitute a panacea to resolving all issues related to the contact of mentally ill individuals with the justice system. Mental health courts must be accompanied by other intervention strategies for persons with mental health problems at all stages of the criminal justice process.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.010 |
| 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".