Evaluation of Publicly Accessible Child Protection in Sport Education and Reporting Initiatives
Bibliographic record
Abstract
Despite sport being a vehicle through which youth may achieve positive developmental outcomes, maltreatment in the youth sport context remains a significant concern. With increased athlete advocacy and research demonstrating the high prevalence of maltreatment in sport, and the urgent need to address it, many international organisations have created child protection in sport initiatives. Of particular focus to athletes and researchers is the provision of evidence-based comprehensive education and independent reporting mechanisms for athletes who experience harm. The current study examined the extent to which the publicly accessible information provided by three sport-specific child protection organisations regarding education and reporting is aligned with recommendations provided by researchers and athletes. With regard to education, the findings highlight accessibility, programming for various stakeholders, and coverage of topics of interest (e.g., forms of harm and reporting processes). However, educational information about equity, diversity, and inclusion and information on how to foster positive environments in sport was lacking. For reporting mechanisms, results showed that each organisation’s approach to receiving reports of maltreatment varied, including their ability to directly intake, investigate, and sanction instances of maltreatment. The findings are interpreted and critiqued considering previous literature and recommendations for future research and practice are suggested.
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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 | 0.239 | 0.335 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".