Human Rights in Youth Sport: A Critical Review
Bibliographic record
Abstract
Child abuse, protection and welfare in sport have come to our attention over the past 10 to 15 years through a number of infamous cases such as Paul Hickson, former British swimming coach, jailed for sexual assaults on young swimmers over 20 years (Brackenridge, 2001) and Graham James, former Canadian professional ice hockey coach, convicted for sexual offences against boys in the game (Kirby et al., 2000). Such cases represent the ugliest side of sport when we want to believe that youth sport represents all that is best in life. A host of questions arise from children’s engagement in youth sports but the overarching question addressed here by Paulo David is ‘Can the integration of human rights in the sport system improve its quality, and the status of athletes, including its youngest ones? ’ (p. 262). Oddly, despite a large literature on youth sports, and sociological critiques from as long ago as 1979, when Rainer Martens and Vern Seefeldt launched their Bill of Rights for the Young Athlete, the human rights impli-cations per se of involving children in competitive sports have barely been examined before (an exception is Grenfell and Rinehart, 2003). The human rights of young
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| 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".