When is a Drug Not a Drug? Troubling Silences and Unsettling Painkillers in the National Football League
Bibliographic record
Abstract
This paper uses a genealogical approach to explore the conjuncture at which the longstanding but partial and uneasy silence surrounding painkiller use in the National Football League seems increasingly under threat. We historicize and problematize apparently self-evident narratives about painkiller use in contemporary football by interrogating the gendered, racialized and labor-related discourses surrounding Brett Favre’s 1996 admission of a dependency on Vicodin, as well as the latest rash of confessions of misuse by now retired athletes. We argue that these coconstructed and coconstructing moments of noise and silence are part of the same discursive system. This system serves to structure the emerging preoccupation with painkillers in the NFL, with Favre’s admission still working to placate anxieties surrounding the broader drug problems endemic to the league, and failing to disrupt our implicit knowingness about painkiller use, thus reinforcing ongoing cultures of silence and toughness in professional football.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.046 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 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".