Modalités et enjeux du traitement sous contrainte auprès des toxicomanes
Bibliographic record
Abstract
OBJECTIVES: This article is exploring different forms of constraint that are exerted in the field of drug addiction treatment. The objective of this article is to establish benchmarks and to stimulate reflection about the ethical and clinical implications of those constraints in the field of drug addiction treatment. METHODS: This article is presenting a critical review of different forms of constraint that can be exerted in Canada in regard to the treatment of drug addiction. In the first section of the article, a definition of therapeutic intervention is proposed, that includes the dimension of power, which justifies the importance of considering the coercive aspects of treatment. The second section, which represents the core section of the paper, is devoted to the presentation of different levels of constraint that can be distinguished in regard to drug addicts who are under treatment. RESULTS: Three levels of constraint are exposed: judicial constraint, institutional constraint and relational constraint. The coercive aspect of treatment can then be recognized as a combination of all tree levels of constraint. Judicial constraint refers to any form of constraint in which the court or the judge is imposing or recommending treatment. This particular level of constraint can take different forms, such as therapeutic remands, conditions of a probation order, conditions of a conditional sentence of imprisonment, and coercive treatment such as the ones provided through drug courts. Institutional constraint refers to any form of constraint exerted within any institutional setting, such as correctional facilities and programs offered in community. Correctional facilities being limited by their own specific mission, it might have a major impact on the way the objectives of treatment are defined. Those limitations can then be considered as a form of constraint, in which drug users don't have much space to express their personal needs. Finally, relational constraint refers to any form of constraint in which the drug addict might be coerced to treatment under the pressure of people from the immediate environment, such as members of family, friends or employers. Even if this form of constraint is not as obvious as the ones exerted by court and correctional facilities, it has to be considered by practitioners who are evaluating the motivation of drug addicts under treatment. CONCLUSION: Considering the diversity of constraints that are exerted on drug addicts who are under treatment, it appears that we should be always aware of the ethical and clinical challenges facing practitioners every day. The recognition of those constraints can also help to understand how important it is to consider the institutional and social context in which treatment is being provided.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".