Chapitre 3. Les caractéristiques des membres de gangs de trente pays et prédicteurs de l’affiliation
Bibliographic record
Abstract
Un facteur de risque important menant à la délinquance juvénile est l’affiliation aux gangs (Agnew, 2005 ; Gatti et coll., 2005 ; Klein et Maxson, 2006 ; Weerman et Esbensen, 2005). Les recherches font état de la « surcriminalité » des jeunes membres, impliqués dans 50 % à 86 % des actes délinquants commis (Bradshaw, 2005). Comme le mentionnent Battin-Pearson et ses collaborateurs (1998, p. 1), « gang membership intensifies delinquent behaviour. From the earliest to the most recent investigat...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".