Government Sponsored Professional Sports Coaches and the Need for Better Child Protection
Bibliographic record
Abstract
The recent media publicity given to the case of Amy Gerhing, the young Canadian teacher acquitted of having a sexual relationship with two of her pupils is in marked contrast to the lack of interest shown to the later cases of Gary Hinds, John Glyn Jones, Mike Edge, Matthew Pedrazzini, Paul North, Frank Slatterwaite, George Ormond and others, all sports coaches who have been convicted of sexually abusing the children they train. This lack of interest is reflected in the recently published Department for Culture, Media and Sport and Sport England Final Report of the Coaching Task Force, a document that sets out recommendations for the future of coaches and coaching in English sport. In amongst the Report’s 84 pages only one sentence makes any mention of the protection of the children these 3,000 coaches have the potential to be training. This article briefly discusses the Report’s proposals, the current state of child protection in sport in England and Wales and argues that with the advent of the publicly funded professional coaches recommended in the Report, the time has come for sport to be made subject to more areas of child protection law than at present.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".