Safeguarding the child athlete in sport: a review, a framework and recommendations for the IOC youth athlete development model
Bibliographic record
Abstract
Participation in sport has many physical, psychological and social benefits for the child athlete. A growing body of evidence indicates, however, that sport participation may have inherent threats for the child's well-being. The subject of safeguarding children in sport has seen an increase in scientific study in recent years. In particular, there is increasing emphasis on identifying who is involved in abuse, the context of where it occurs and the identification of the various forms of abuse that take place in the sporting domain. Safeguarding principles developed by the International Safeguarding Children in Sport Founders Group are presented along with 8 underlying pillars which underpin the successful adoption and implementation of safeguarding strategies. This safeguarding model is designed to assist sport organisations in the creation of a safe sporting environment to ensure that the child athlete can flourish and reach their athletic potential through an enjoyable experience. The aim of this narrative review is to (1) present a summary of the scientific literature on the threats to children in sport; (2) introduce a framework to categorise these threats; (3) identify research gaps in the field and (4) provide safeguarding recommendations for sport organisations.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".