Why don’t you Dope? A preliminary analysis of the factors which influence athletes decision not to Dope in Sport
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this paper is to examine why athletes do not dope in sport. The research treats the ‘problem’ of doping as an issue of ‘control’ and draws on control theory (Hopwood, 1974; Byers, 2013) to analyze athletes choices not to engage in doping. Semi-structured interviews were conducted with cur- rent Canadian athletes, former athletes, coaches, and officials from seven different sports that competed in the CIS (Canadian Interuniversity Sport), national and international events, professional sport, Pan American Games, provincial teams, and World University Games. In total, 20 interviews were conducted with 7 female and 13 male participants. Results indicate that an over- abundance of administrative formal control mechanisms may be creating confusion and inefficiency in the doping control system. More powerful control mechanisms such as social and self-controls seem to be operating amongst athletes and issues of trust and the role of emotion are significant concepts that re- quire further research in this context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it