Former Athletes' Illness Stories of Brain Injuries: Suspected Chronic Traumatic Encephalopathy and the Entanglement of Never‐Aging Masculinities
Bibliographic record
Abstract
Examining former athletes' health‐related beliefs and behaviors on the long‐term effects of concussions and potentially developing chronic traumatic encephalopathy (CTE) offers a domain to understand how men renegotiate their masculinities. In this paper, we explore how the cultural production of the concussion crisis shapes the ways in which men athletes make sense of self and their masculinity in the face of declining health. Drawing on in‐depth interviews with 27 male, former athletes, this article examines the multiple ways in which gender shapes their experience and treatment of traumatic brain injuries or suspected CTE. We show how men are re‐negotiating their aging masculinities through illness narratives and how the cultural production of the concussion crisis in sports shapes these narratives. We break down our analysis into three sections: (1) reflections of chaos narratives and stories of never‐aging masculinities, (2) the ways the concussion crisis shapes their restitution narratives, and (3) quest narratives combining never‐aging and aging masculinities. Whether or not these athletes have or are treated for CTE, we argue that they reformulate their masculinity to regain control over their manhood and to feel a sense of relief.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".