Stunt performers’ reluctance to self-report head trauma: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Mild traumatic brain injuries receive voluminous attention in the research literature, but this is confined almost entirely to sports and military contexts. As an occupation, performing stunts in film, television, and entertainment places the head at high risk of repetitive impact and whiplash, but stunt performers do not enjoy the same level of healthcare supervision and access as that provided to sports participants. Therefore, the aim of this study was to evaluate stunt performers' qualitative perceptions of reporting and management of head trauma in their industry. METHODS: After giving their informed consent, 87 motion picture and television stunt performers responded to a query about their views of ways to improve how stunt performers' occupational head trauma-specifically head impacts and head whips that could cause a concussion-are reported and managed. We analyzed their responses via content and thematic analyses. Two researchers independently marked and categorized key words, phrases, and texts to identify codes that described participants' comments. They then revised, discussed, and resolved coding discrepancies through consensus to establish inter-coder reliability. Next, we identified thematic patterns that described participants' understanding of the stunt performer industry and what must change to facilitate reporting of head trauma. We derived themes from data that occurred multiple times, both within and across short answer responses. RESULTS: We identified three primary themes cited by the stunt performers as needs in their industry: (1) Need to Reduce the Stigma of Reporting a Stunt-Related Injury, (2) Need to Eliminate the "Cowboy Culture," and (3) Need to Improve the Quality of the Work Environment. CONCLUSIONS: Stunt performers are crucial members of a global entertainment industry valued at approximately US$100 billion annually. A large segment of the world's population consumes their work in motion pictures, television, and live entertainment. When they are given an anonymous opportunity to speak, stunt performers offer insight into and recommendations for industry changes-primarily cultural and educational in nature-that could improve their physical and mental health, career longevity, and employability when they are confronted with head trauma.
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.
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 | 0.025 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".