Offside: An International Comparison of Group Sexual Assault in Competitive Young Men’s Ice Hockey
Bibliographic record
Abstract
Athlete-perpetrated sexual violence within hockey has historically been concealed and \nrarely acknowledged within academic literature and public discourse in Canada and \ninternationally. To analyze group-sexual assault cases in young men’s hockey in Canada and the \nUnited States at the high-school, intercollegiate, and junior level, this study utilized an \nunobtrusive case-study approach, revealing the relative prevalence in which group sexual \nassaults occur, the common characteristics of these cases, and how institutions such as hockey \norganizations and the criminal justice system have responded to this form of gender-based \nviolence. Two primary sources of unobtrusive data were used within this study, including: 1) \ndocumentation accessed through the online legal document repositories vLex, CanLii, and \nWorldLii, and 2) documentation accessed through online media article archives Access Word \nNews, Google News, and Canadian Newsstream. In total, 30 cases, including 20 in Canada and \n10 in the United States, were analyzed. \nThrough the analysis of 30 cases of group sexual assault, there were seven key findings, \nincluding: 1) accused players are rarely held accountable, 2) Canadian Junior hockey players are \ndisproportionately represented in reports of athlete-perpetrated group sexual assault, 3) accused \nplayers often receive support from their coaches, team management, and the community, while \nvictims often do not, 4) Canadian and American hockey organizations respond comparatively \ndifferently when players are accused of sexual assault, 5) disciplinary responses were lower \namong Canadian Junior hockey cases, compared to American cases, 6) in many cases, players \nwho faced charges of sexual assault could advance their careers to higher professional playing \nlevels (such as the National Hockey League), and 7) with increased media attention, public outcry, and disciplinary responses more recently, a significant shift in tolerance and responses to \nthese incidents has occurred over time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".