Crime prevention or positive youth development? An evaluation of the Nunavik youth hockey development program
Bibliographic record
Abstract
The Nunavik Youth Hockey Development Program (NYHDP) targets Inuit youth in all 14 communities of Nunavik and is funded under a crime prevention strategy by the local government (Bean & Haman, 2015). The program consists of two components: a recreation-based and a competitive program. Recently, the local government decided to cancel the competitive program based in part on an independent evaluation that concluded the program did not achieve its intended goal of crime prevention. In response to this decision, at the request of program's founder (Joe Juneau, NHL), two members of the study team spent a week conducting a case study of the final select Bantam/Midget Girls Team at a training camp in Inukjuak to examine the perceived impact of the NYHDP. Over 8 days we conducted 10 individual and 2 focus group interviews with program leaders, coaches, teachers, players, parents of players, community leaders, and social support workers. Additionally, we participated in and observed hockey practices and classroom sessions. The athletes attending this camp faced many challenges in their daily life, including suicide, emotional/physical abuse, and substance use. The program was perceived positively and offered participants an opportunity to escape the challenges of their everyday lives. However, the program outcomes did not appear to be directly related to crime reduction per se. Additionally, while there was a link between the NYHDP program and education, this link was tenuous and could be strengthened. The NYHDP may be better characterized as a youth development intervention rather than a crime prevention program.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".