The Penalty That’s Never Called: Sexism in Men’s Hockey Culture
Bibliographic record
Abstract
During the summer of 2022, Hockey Canada faced a reckoning regarding its outright denial of the ways in which gender-based violence is a part of hockey culture. This paper shares data from a study that involved qualitative interviews with semi/professional men’s ice hockey players regarding their resistance to the expectations of hypermasculinity in hockey culture. Hypermasculinity is the elevated status of traits that promote violence, stoicism, and aggression and that privileges the locker-room code of silence. Participants spoke about the dangers of playing through pain as well as the precarity of their roles on their teams due to policing strategies that put the team before anything else. The participants were less direct about the ways sexism and misogyny are used as a means to improve team bonding and performance, yet stories of sexism and misogyny were riddled throughout the data. Our analysis brings together Bourdieu’s concept of misrecognition to gain understanding as to why sexism remains/ed silent and Freire’s conscientization to promote more dialogic encounters to clear the air of sexism in men’s ice hockey.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.030 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".