Child Protection in Sport: Reflections on Thirty Years of Science and Activism
Bibliographic record
Abstract
This paper examines the responses of state and third sector agencies to the emergence of child abuse in sport since the mid-1980s. As with other social institutions such as the church, health and education, sport has both initiated its own child protection interventions and also responded to wider social and political influences. Sport has exemplified many of the changes identified in the brief for this special issue, such as the widening of definitional focus, increasing geographic scope and broadening of concerns to encompass health and welfare. The child protection agenda in sport was initially driven by sexual abuse scandals and has since embraced a range of additional harms to children, such as physical and psychological abuse, neglect and damaging hazing (initiation) rituals. Whereas in the 1990s, only a few sport organisations acknowledged or addressed child abuse and protection (notably, UK, Canada and Australia), there has since been rapid growth in interest in the issue internationally, with many agencies now taking an active role in prevention work. These agencies adopt different foci related to their overall mission and may be characterised broadly as sport-specific (focussing on abuse prevention in sport), children’s rights organisations (focussing on child protection around sport events) and humanitarian organisations (focussing on child development and protection through sport). This article examines how these differences in organisational focus lead to very different child protection approaches and “solutions”. It critiques the scientific approaches used thus far to inform activism and policy changes and ends by considering future challenges for athlete safeguarding and welfare.
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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 | 0.044 | 0.023 |
| 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 | 0.092 |
| Scholarly communication | 0.026 | 0.019 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.017 | 0.020 |
| Insufficient payload (model declined to judge) | 0.006 | 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".