Outdoor Sport in Extreme Heat: Capturing the Personal Experiences of Elite Athletes
Bibliographic record
Abstract
Abstract Heat stress from the environment can be detrimental to athletes’ health and performance. No research, however, has explored how elite athletes conceptualize and experience heatwaves and climate change. Utilizing a qualitative approach, this study examined elite athletes’ perceptions, experiences, and responses to extreme heat in relation to climate change and explored the use of their platforms for climate activism. Fourteen elite athletes from the United Kingdom, Australia, the United States, Sweden, and Canada, who represented 10 different sports including race walking, netball, and cricket were recruited using snowball sampling. Data were collected using semistructured interviews. Thematic analysis revealed four broad themes. The first theme reflected uncertainty surrounding the causes of heatwaves and the impact of heat on athlete health and performance. The second theme reflected care and concern for sport and society, including concern for the well-being of athletes and spectators, the impact of heat on facilities and participation at the grassroots level, and how the nature of sport may change in the future. The third theme referred to the implications of heatwave experience on athlete health and performance, and how experience affected individual and organizational preparedness. The fourth theme referred to enablers and barriers to successful climate change communication. This study contributes to the sport ecology literature by introducing the subjective heat experiences of elite athletes. Educating athletes and event organizers about the impacts of heat on sport participation is imperative to increase awareness and, it is hoped, to limit illness for those training and competing.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".