Behaviours and Beliefs Related to Whistleblowing Against Doping in Sport: A Cross-National Study
Bibliographic record
Abstract
Background: Whistleblowing has been recognized as an important deterrent of doping in elite competitive sport. The present study examined athletes' knowledge of external whistleblowing channels and on how and where to report doping misconduct, perceived trust in different whistleblowing reporting channels, whistleblowing behaviour and athletes' reasons for reporting (or not) doping misconduct. Methods: = 171) completed a structured questionnaire on demographics, knowledge of different whistleblowing channels, perceived trust in internal and external whistleblowing channels, past whistleblowing behaviour and reasons for reporting (or not) doping misconduct. Results: = 0.012) respectively. However, British athletes reported the lowest scores on knowledge of how and where to report doping misconduct, as compared to athletes from Greece and Russia. The majority of respondents reported greater trust to their coach or a club manager than to other whistleblowing channels, however, responses regarding other channels varied by country. Among athletes who detected doping misconduct 62% of athletes did not report it, while 38% reported it. Reasons for and against reporting doping misconduct reflected in eight themes that were identified using thematic analysis. Conclusion: Athletes showed low awareness of external whistleblowing channels and they predominantly trusted internal whistleblowing channels. Sportspersonship, confidence in resources and personal benefits were among the reasons that facilitate reporting doping misconduct. The present findings indicate that cultural context may play a role in the ways athletes perceive whistleblowing, and this should be taken into account by future interventions to promote the reporting of doping misconduct.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".