Women With Hyperandrogenism in Elite Sports: Scientific and Ethical Rationales for Regulating
Bibliographic record
Abstract
The recent implementation by some major sports-governing bodies of policies governing eligibility of females with hyperandrogenism to compete in women's sports has raised a lot of attention and is still a controversial issue. This short article addresses two main subjects of controversy: the existing scientific basis supporting performance enhancing of high blood T levels in elite female athletes, and the ethical rationale and considerations about these policies. Given the recently published data about both innate and acquired hyperandrogenic conditions and their prevalence in elite female sports, we claim that the high level of androgens are per se performance enhancing. Regulating women with clinical and biological hyperandrogenism is an invitation to criticism because biological parameters of sex are not neatly divided into only two categories in the real world. It is, however, the responsibility of the sports-governing bodies to do their best to guarantee a level playing field to all athletes. In order not cloud the discussions about the policies on hyperandrogenism in sports, issues of sports eligibility and therapeutic options should always be considered and explained separately, even if they may overlap. Finally, some proposals for refining the existing policies are made in the present article.
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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 | 0.071 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.041 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.028 | 0.026 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".