A Critical Examination of Child Protection Initiatives in Sport Contexts
Bibliographic record
Abstract
With the broadening of focus on child maltreatment beyond intra-familial settings, there is growing awareness of occurrences of maltreatment within the sport context. Millions of children participate in organized sport annually, and despite a tendency to view sport as a context by which to enhance the overall health and development of children, it is also a context in which children are vulnerable to experiences of maltreatment. The well-documented power ascribed to coaches, the unregulated nature of sport and a “win-at-all-costs” approach contribute to a setting that many propose is conducive to maltreatment. A number of high profile cases of sexual abuse of athletes across several countries in the 1990s prompted sport organizations to respond with the development of child protection measures. This study examined seven child protection in sport initiatives in terms of the extent to which they originated from research, had content that was consistent with scholarly work and were evaluated empirically. The findings indicated that these initiatives were not empirically derived nor evaluated. Recommendations are made to more closely align research with these initiatives in order to protect children and to promote a safe and growth-enhancing experience for young participants in sport.
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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 | 0.019 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".