From Silence to Surveillance: Examining the Aftermath of a Canadian University Doping Scandal
Bibliographic record
Abstract
This paper examines a football doping incident that occurred at the University of Waterloo (UW) in Canada, and critically analyzes the doping policy recommendations for intercollegiate sport sparked by the scandal. In March 2010 a police raid led to the discovery of a large quantity of performance-enhancing drugs at a home linked to a former student-athlete, which resulted in an entire football team being subjected to mandatory drug testing. After the release of the test results, a task force was formed by the Canadian Centre for Ethics in Sport (CCES) to investigate doping in Canadian sport. Using a triangulation approach, which includes a case study of the UW doping scandal, semistructured interviews with student-athletes, and policy analysis of the reports that transpired, we critically examine the potential effects and scope of applicability of the new recommendations put forward by the task force. In critiquing the resulting recommendations, this paper cautions that replacing a culture of silence with a culture of surveillance can have detrimental effects in the fight against doping 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 | 0.017 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.050 | 0.028 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.006 | 0.011 |
| 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".