Bibliographic record
Abstract
Sexual violence on college campuses is not a new issue, however, the current media spotlight has brought greater public attention to this problem. Yet, despite this attention, there continues to be incidences of sexual violence across university campuses, and in university athletics in particular. In more than 100 cases of sexual violence on Canadian university campuses over a ten-year span, 23% involved university athletes as alleged perpetrators (Quinlan et al.). Given that competitive athletes compose between 1-3% of the university student population in Canada, they are over-represented in reported cases of sexual violence (Quinlan et al.), which suggests that sexual violence in university sport is particularly problematic. In this paper, this issue is addressed by asking how ruling relations inform institutional responses to sexual violence. First, to explore this question a literature review of sexual violence in sport is provided. Second, a description of how the ruling relations of organizations as a conceptual framework is outlined. Third, a consideration of the institutional responses to two cases of sexual violence in university athletics reported in the Canadian media are described. Following a discussion concerning these cases, suggestions are offered that address sexual violence in Canadian university sport, which may be translatable to other contexts.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".