« Quand le problème, c’est aussi la solution » : les gangs de rueet la multiplication des systèmes normatifs de prise en charge pénale
Bibliographic record
Abstract
Dans cet article, l’auteure entend démontrer que la façon dont on a problématisé les gangs de rue, c’est-à-dire de façon à la fois trop large et trop restreinte, a mené à la multiplication des systèmes de prise en charge pénale, en particulier à l’utilisation combinée des systèmes normatifs que constituent le droit criminel, le droit pénal réglementaire et le droit administratif de l’immigration, et à une expansion de la sphère de contrôle répressive. Or, le recours concurrent à différents systèmes normatifs a des conséquences dramatiques pour les communautés visées par les gangs de rue, essentiellement des communautés pauvres et à forte prédominance ethnique, exacerbant ainsi les tensions avec les représentants de l’État, entretenant les préjugés et contribuant au maintien de leurs conditions précaires et à la production de la délinquance juvénile.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".