Temporal and Developmental Risk Factors for Sexual Harassment and Abuse in Sport
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent revelations of sexual misconduct by sports coaches have challenged long-held beliefs in the educational value of sport, yet there is very little knowledge about the dynamics of sexual exploitation in sport upon which to base improvements in the practice of sports coaching or teaching. Earlier inductive research by Brackenridge in Britain established a set of hypothesized risk factors for sexual abuse in sport which have subsequently been reinforced by the results of survey research on elite athletes in Canada. However, risk analysis for sexual abuse in sport has not yet been framed within a temporal or developmental sequence, nor sufficiently differentiated between elite and recreational levels of sport, or between coach-initiated and peer-initiated abuse. This article reports selected findings from a Dutch qualitative study of 14 athletes who have survived sexual abuse in sport. The aim of the study was to identify risk factors that influence sexual abuse and harassment and to analyse which risks might be diminished through a prevention policy implemented by sport organizations. The Dutch study reinforces the earlier risk factor analyses but extends them by putting forward a preliminary temporal model of risk in sport that integrates offender behaviour with athlete and situational factors. On the basis of this model, suggestions are made to assist early diagnosis and prevention of sexual harassment and abuse by authority figures in sport.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it