Jeunes à risque ? Sens des pratiques dites à risque et sortie de la rue
Bibliographic record
Abstract
Face à l’abondance de chiffres concernant les risques que les jeunes encourent dans la rue ou font encourir aux autres, on peut avoir tendance à oublier que leurs comportements dits « à risque » constituent les manifestations d’enjeux plus profonds. Alors que l’idéal d’autoréalisation individuelle valorise certaines formes de prise de risques, on constate simultanément la présence importante au sein de nos sociétés d’une obsession sécuritaire qui vise la gestion des populations à risque. À partir d’une enquête auprès de jeunes sortis de la rue réalisée à Montréal, le présent article vise à mettre en lumière l’écart entre le sens attribué par les jeunes à la marginalité et à la normalité et la tendance politique à privilégier des approches épidémiologique et sécuritaire à l’égard de ces populations. Il se conclut par une analyse des effets de ces approches en termes de reconnaissance sur le processus de sortie de la rue de ces jeunes.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".