L’injonction thérapeutique à l’égard des toxicomanes : comparaison des systèmes français et québécois
Bibliographic record
Abstract
In Canada, the total amount of accusations, in compliance with the laws on drugs, show a slight but constant progression. More than half of the sentences for drug-linked offenses have lead to incarceration, a third of the people sentenced for a simple drug possession have been jailed. The relevance of these sentences, making the Canadian detention centres populated with more drug addicts than the rehabilitation centres, is questionable. In France, legislation is mostly based on the December 31st, 1970 law: drug use and trafficking are severely punished. However, for a first arrest, the prosecutor can enjoin the arrestee to treatment: this is what is called therapeutic injunction. Even though therapeutic injunction spares substance users from a jail term, some limitations are encountered this measure is selective, based on social and judicial criteria, making it more forgiving than the average characteristics of drug addicts, it is only accepted and applied by half of the subjects. A specific inquiry has been done in a department in the Paris region, where drug addiction activity is abundant, and suggested a preventive role for the injunction in cases of recidivism. Global appreciation of the therapeutic injunction remains nuanced in a context of new measures in drug addiction, but it translates into the increasing necessity to introduce professional networks between the judicial and sanitary systems, intended for a young population dealing with the modern difficulties of social adaptation and high risk behaviour.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".