Bibliographic record
Abstract
This article examines the problem of parental aggression in minor hockey in the Canadian province of Quebec. Findings of the study are based on 30 semi-structured, qualitative interviews with minor hockey stakeholders in Quebec, including parents, coaches, referees and league executives. Interviews were conducted in both French and English. All 30 study participants observed parental violence and harassment while watching, coaching, and/or refereeing minor hockey and shared their perspectives on why parental aggression occurs in Quebec minor hockey. Drawing on Spaaij’s (2014) social-ecological model, we introduce a social-ecological model specific to the Canadian minor hockey context, which includes structural, social environmental, situational, interpersonal and individual. Moving from the structural to the individual, these factors include 1) levels of racism, xenophobia, and identity-based antagonisms in society, 2) high parental expectations related to their children’s performance, team success, and development, the high cost of hockey, hockey’s cultural significance as Canada’s game, and the lack of leverage leagues and arenas to punish spectator misbehaviour, 3) the layout of arenas and the rules around alcohol at particular arenas, perceived ‘bad’ refereeing, illegal play, or unfair ice time allotments, higher levels of on-ice violence and injuries, and rivalries, 4) spectators trying to coach from the stands and/or yelling at referees and coaches, and 5) the behaviour and demeanour of spectators, coaches, referees, and even the players on the ice.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".