Bibliographic record
Abstract
Hockey Canada, the national federation for ice hockey, faced a governance crisis in 2022. The crisis arose from the settlement of a 2018 sexual assault claim involving members of the World Junior hockey team. This chapter charts the governance scandal, arguing that while Hockey Canada did not legally err, its failure to engage in socially responsible governance led to a loss of legitimacy. As the settlement involved a non-disclosure agreement, this chapter also traces the use of non-disclosure agreements in settlements of sexual misconduct cases, including those in sport. The chapter ends with some reflections on what a change in the landscape for non-disclosure agreements will mean for sports governance, and what the Hockey Canada crisis reveals about organisations who live up to legal standards, but not societal standards.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".