“<i>The process isn’t a case of report it and stop”</i>: Athletes’ lived experience of whistleblowing on doping 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
Whistleblowing is effective for exposing doping in sport, garnering increased support and promotion within the global anti-doping community. However, limited attention has been afforded towards understanding the doping whistleblowing process. In response, the authors convey a sense of the whistleblowing context by using the actual words of whistleblowers to illuminate their experience. To achieve this aim, the authors have adopted a narrative approach. Three doping whistleblowers were interviewed regarding their lived experiences of whistleblowing on doping and the data has been represented in the form of one composite creative non-fiction story. The story narrates the whistleblowing experience as a process whereby individuals must (a) determine what they witnessed and experienced was doping, (b) make the decision and take action to report it, and (c) deal with the myriad of consequences and emotions. It also highlights the dilemma faced by whistleblowers who are likely equally compelled to adhere to the moral of loyalty and fairness; yet in this context they are unable to do both. Stemming from the story presented and the forms of retribution experienced, the authors offer practical suggestions for sporting organisations to address in order to empower others to whistleblow on doping in sport. Specifically, organisations should establish and implement whistleblowing policies that: (a) provide protection for whistleblowers, (b) mandate whistleblowing education, and (c) identify an independent person for individuals to seek guidance and support from before, during and following the act of whistleblowing.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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