Transgender athletes and Canadian sport policy: a story of stigma and precarity
Bibliographic record
Abstract
Policy can serve as a form of institutionalised stigma, working to create and maintain discrimination against groups of people. Some Canadian National Sport Organizations (NSOs) have developed policies that address transgender inclusion within sport. However, where these policies exist, they vary in their approaches to inclusion of transgender persons. This article examines how Canadian sport policies prohibit and/or police transgender persons’ participation in sport. In 2019, the publicly available policies of 53 NSOs were reviewed to determine the presence and content of so-called transgender inclusion policies, as well as policies related to equity, discrimination and harassment. At the time of the study, only 17 of the 53 NSOs had policies specifically related to transgender inclusion. In this study, we review these policies to understand the varying approaches to transgender inclusion in Canadian NSOs. We classified the NSOs into three broad categories: inclusive (n = 11), problematic (n = 1) and prejudicial (n = 5), in relation to naming, disclosure and medical specifications. Using Judith Butler’s concept of precarity, we demonstrate that participation in sport is a precarious choice for transgender athletes, as most NSO policies lacked clear guidance on inclusion and there were next to no policy statements on gender non-conforming people. The development of inclusive policy within sport should be proactive, actionable, consistent with best practices and must include meaningful conversations with transgender and gender non-conforming athletes, coaches and officials.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.083 | 0.050 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".