A public health approach to maltreatment in sport: a case study of Hockey Canada
Bibliographic record
Abstract
Maltreatment in sport has gained unprecedented attention in Canada, prompting significant policy reforms targeting safer sport environments. This paper examines how one of Canada’s largest national sport organisations (NSOs), Hockey Canada, responded to a recent mandate to strengthen safe sport policies. Using a descriptive case study design, we identify three key developments in Hockey Canada’s approach to maltreatment: internal and external policy convergence with national standards; enhanced policy implementation via clearer rules, enforcement mechanisms, and mandatory training; and improved policy evaluation through systematic data collection and transparency. These developments illustrate the substantive role NSOs can play in a public health approach to prevent athlete maltreatment by addressing risk and protective factors at multiple levels. We also point to ongoing challenges related to organisational culture, government oversight, and the need for empirical evaluation. Our findings contribute to sport policy discourse by highlighting both the potential and the limits of NSO-led interventions in fostering safe sport environments.
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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 | 0.001 | 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) | 0.000 | 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".