Weapons and Violence Among Male Delinquents: An International Comparative Study
Bibliographic record
Abstract
Abstract Despite growing concerns about youth violence, little research has been conducted in countries other than the USA specifically about the prevalence and actual use of weapons to threaten or harm others. This study employed the same questionnaire and methods to recruit 888 male delinquent youth in Toronto, Montreal, Philadelphia and Amsterdam. Two contrasting perspectives on the importance of firearms restriction in preventing youth violence - futility and availability - guide the discussion. Specifically, detained and dropout youth appear to have quite ready access to firearms, regardless of national gun control laws. On logistic regression analysis, the strongest independent predictors of four weapon related violent outcomes were site, prior delinquency and victimization; notably for gun violence, selling cocaine/crack, history of gang fights and living in neighbourhoods where drug selling was conspicuous, were significant. The high levels of gun involvement and weapons related violence among Toronto and Montreal youth were unexpected. The Canadian youth justice system may be selecting more serious delinquents for incarceration than those in the USA and the Netherlands. These results may also be a harbinger of greater gun availability, or reflect greater willingness of delinquent youth to arm themselves, than in the past. Since baseline data about firearms carrying, acquisition and use have not been collected previously in Canada, it will be important to monitor these trends.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".