Prévalence des troubles de santé mentale, motivation au traitement et pertinence des suivis thérapeutiques chez les délinquants sous surveillance dans le District Montréal métropolitain
Bibliographic record
Abstract
We have conducted a research on therapeutic follow-ups with delinquents on parole, in Metropolitan Montreal, by analyzing the following characteristics: the clientele's professional care, the proportion of subjects who use the therapeutic follow-ups during their jail term and parole, the relevance of treatment, and the beneficiary's legal status of parole. According to our results, 81% of the subjects had classified clinical diagnostics at DSM III-R; 23,33% for double diagnostics; 14% for substance abuse and 6,67% for mood swings. 85,3% of the clients receive treatment given by psychologists, making it the most popular. Officers estimate that therapeutic follow-ups are pertinent in 91,9% of the cases, when the treatments are given to individuals with behavior problems or mental health disorders, and in 86,6% of the cases, when dealing with clients who are less motivated to take treatment. The results also show that 61,3% of the subjects were involved in therapeutic follow-ups in the last months of incarceration. This percentage proves that subjects who receive psychological treatments during their incarceration are the most likely to continue during parole. Generally speaking, the results were very encouraging and contradict some statements to the effect that there is a lack of motivation in delinquents and that therapeutic follow-ups offered to parole clientele are impertinent. Results also show that the clientele who remains in psychological treatment is motivated to continue the treatment and that these follow-ups are considered pertinent by the clientele.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".