Athlete health and safety at large sporting events: the development of consensus-driven guidelines
Bibliographic record
Abstract
All sport events have inherent injury and illness risks for participants. Healthcare services for sport events should be planned and delivered to mitigate these risks which is the ethical responsibility of all sport event organisers. The objective of this paper was to develop consensus-driven guidelines describing the basic standards of services necessary to protect athlete health and safety during large sporting events. By using the Knowledge Translation Scheme Framework, a gap in International Federation healthcare programming for sport events was identified. Event healthcare content areas were determined through a narrative review of the scientific literature. Content experts were systematically identified. Following a literature search, an iterative consensus process was undertaken. The outcome document was written by the knowledge translation expert writing group, with the assistance of a focus group consisting of a cohort of International Federation Medical Chairpersons. Athletes were recruited to review and provide comment. The Healthcare Guidelines for International Federation Events document was developed including content-related to (i) pre-event planning (eg, sport medical risk assessment, public health requirements, environmental considerations), (ii) event safety (eg, venue medical services, emergency action plan, emergency transport, safety and security) and (iii) additional considerations (eg, event health research, spectator medical services). We developed a generic standardised template guide to facilitate the planning and delivery of medical services at international sport events. The organisers of medical services should adapt, evaluate and modify this guide to meet the sport-specific local context.
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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 | 0.382 | 0.472 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.014 | 0.016 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".