Sex, drugs and science: the IOC’s and IAAF’s attempts to control fairness in sport
Bibliographic record
Abstract
This paper traces the history of two important policies in sport: rules against drugs and ‘ambiguous’ athletes in women’s events. We identify three phases in the work of the International Olympic Committee’s and International Amateur Athletic Federation’s medical committees: (1) from the mid-1960s to the 1970s, the medical grounding of the committees and the members’ worldviews encouraged the groups to enlist scientific techniques to solve drug use and sex ambiguity issues; (2) from the 1970s to the 1980s, administrative confusion underscored both committees, but scientific personnel gained legitimacy and furthered their own agendas; and (3) from the 1980s to the mid-1980s, the seeds of diversion in sex and drug tests were sown. The central finding of this study is that the stakeholders who shaped anti-doping and sex testing policies took for granted concerns regarding ethics and instead increasingly relied upon medical, scientific, and technical practices to define and control fairness 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 | 0.056 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.016 | 0.119 |
| Scholarly communication | 0.022 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.016 | 0.023 |
| Insufficient payload (model declined to judge) | 0.002 | 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".