Youth Gangs in Canada: A Preliminary Review of Programs and Services
Bibliographic record
Abstract
The Canadian Research Institute for Law and the Family (CRILF) was awarded a Crime Prevention Partnership Program grant by the Department of Public Safety and Emergency Preparedness Canada to collect and review information on youth gangs in Canada, as well as to identify programs and services aimed at addressing youth involvement in gang activity. The main objectives of this research were to: (1) Develop a multidimensional conceptual framework of youth involvement in gangs, including gangs with connections to organized crime, in the Canadian context. Factors such as the motivations to join a youth gang, recruitment tactics, organization, activities, and exit strategies are considered in the development of a typology that can be utilized to better understand youth gang involvement. (2) Identify programs and services addressing issues relevant to youth gangs in Canada, such as risk factors, recruitment processes, links with organized crime, and exit strategies. Key program components sought include the geographic location of the program, the target group, the objectives and activities of the initiative, the organization facilitating the program, and its funder. (3) Categorize the program initiatives based on their level of prevention – primary (prevention, raising awareness), secondary (intervention) or tertiary (rehabilitation, exit strategies).
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".