Youth gangs, delinquency and drug use: a test of the selection, facilitation, and enhancement hypotheses
Bibliographic record
Abstract
BACKGROUND: Three different explanations have been given for the observation that adolescent gang members report more delinquent behaviour than their counterparts who do not affiliate with gangs: a) adolescents who commit more crimes join gangs (selection hypothesis); b) gang membership facilitates deviant behaviour (facilitation hypothesis); c) selection and facilitation work interactively (enhancement hypothesis). The aim of this study was to test these hypotheses, while controlling for self-reported delinquency, friends' delinquency, and individual as well as family characteristics. METHOD: The sample included 756 boys first assessed when they attended kindergarten in disadvantaged areas of Montreal. Gang membership was assessed at the ages of 14, 15 and 16 years. Delinquency and drug use data were collected from self-reports and court files at the same ages. RESULTS: Gang members displayed far higher rates of delinquent behaviour and drug use than non-gang members. The results support the facilitation model for transient gang members (i.e., youths in a gang during only one of the three periods considered) and the enhancement model for stable gang members (i.e., youths in a gang for at least two of the periods considered), for person and property offences. The association between gang membership and delinquency persisted after introducing the control variables. Additional analyses showed that the effect associated with belonging to a gang was beyond that of simply having delinquent friends. CONCLUSION: Preventing the creation and participation in such gangs should reduce the frequency of antisocial behaviour during adolescence.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".