Athletes’ perceptions of transgender eligibility policies applied in high-performance sport in Canada
Bibliographic record
Abstract
This chapter presents the results of a small qualitative study designed to gain insight into transgender and cisgender athletes&s; perceptions of fairness in the regulation and inclusion of transgender athletes in high-performance sport. It provides insight into the barriers to inclusive sport that eligibility rules create for transgender individuals, but are not intended to represent all athletes&s; perspectives or ways of thinking. The chapter emphasizes three themes that emerged from the viewpoints shared in the interviews such as: uncertainty about what constitutes a performance advantage in sport, a commitment to fairness, but genuine doubt as to what fairness entails, and connections between participants&s; understanding of fairness and respect. Many researchers have pointed out the continued unfairness of discriminating against transgender athletes, and today high-performance sport remains a sex-segregated space that can condone gender injustice. The resulting information can then be used to design more inclusive sport policies and educational resources for teachers, coaches, athletes, and other stakeholders in sport.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.025 | 0.010 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".