“The coaches always make the health decisions”: Conflict of interest as exploitation in power five college football
Bibliographic record
Abstract
Much research exists on conflict of interest in high-performance sport in the global North. Yet, the research conducted particularly into US college football—a fairly unique social site of athletic labor given that the fact that enormous revenue is produced by professionalized work that is not compensated—is largely quantitative in nature. In this study, we conducted semi-structured qualitative interviews with twenty-five former power five football players Based on our conversations with former college football players in order to interrogate in a more granular way how and why conflict of interest undermines health and safety in the sport. We found that the well-being of college football players is consistently jeopardized because of the financial imperatives that shape the sport and compromise the care players receive from medical practitioners beholden to the team's ‘need’ to win at all costs. In addition to the inherent concerns this raises about the state of medicine in college athletics, we would also contend that the experiences of the players we spoke to offer a crucial intervention into the debate over ‘exploitation’ in college sport. While exploitation is generally understood in economic terms based on the question of how and to whom the value produced through the commodity spectacle of college sport is distributed, we contend that it should also be understood in terms of the attendant harms. The testimony in this article contributes to the literature on conflict of interest principally by providing some of the most rich and evocative available testimony about how and why conflict of interest occurs and what the implications are for the players whose care is compromised by it.
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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 | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.065 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".