Regards croisés sur les politiques de prise en charge des toxicomanes : France-Québec
Bibliographic record
Abstract
ln France, like in Quebec, drug addiction is a truly important issue of public health to which government needs to organize a clear solution. Political choices made about how to attend drug addicts are essential to fight against the drug phenomenon and its harmful effects. Those two political and geographic entities, linked by history and culture, have been trying mostly since the 20th century to come forth with solutions, in adopting a repressive approach in the first place before incorporating a limitative dimension of drugs' harmful effects and risks in a second place. Through this adjunction of a prohibitive policy and harm reduction policy , what are the rapprochements and divergences of the care of drug addicts between Quebec and France? ln approaching both of these policies, by studying their concepts, their affirmations and practices, an existence of similarity is found. Some light differences will however show up and Quebec may seem to be more of an innovator in this field. The results of this comparison might be signs of a new reflexion deeper on the best solution to bring to the drug addict issue.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".