Athlete maltreatment in sport: Protocol for a scoping review
Bibliographic record
Abstract
Research on maltreatment in sport demonstrates detrimental effects on athletes' well-being, and recent news reports highlight the pervasiveness of this issue. However, inconsistencies in defining and operationalizing athlete maltreatment in sport have resulted in issues with conceptual clarity that limits current research, practice, and monitoring within and across sport sectors. This scoping review will synthesize the scientific literature on athlete maltreatment in sport and identify current knowledge gaps for research and practice. The review objectives are to: (1) map how maltreatment has been conceptualized and operationalized in the literature; (2) identify and describe the types of athlete maltreatment that have been investigated; and (3) explore current trends in research approaches and methods applied to the study of athlete maltreatment. An established six-stage scoping review methodology will be applied, as well as field-specific guidelines for community advisory group consultations. The protocol will be conducted over a one-year time frame and has been registered in advance (https://osf.io/r7ycp/overview). Relevant sources will be identified using a systematic search strategy across six electronic databases. Study screening procedures will occur in duplicate using pre-determined eligibility criteria. For inclusion, articles must address the concept of maltreatment among athletes (of any age, sport, or competition level), and contain original peer-reviewed research. Extracted data will be analyzed using qualitative content analysis and descriptive statistics. Preliminary results will be presented to community advisors (e.g., athletes, coaches, sport administrators, clinicians, policy writers, researchers) to contextualize findings and prioritize actionable recommendations to improve sport systems. Results will be published in a peer-reviewed journal and presented at academic conferences for sport leaders and researchers with the aim of informing measures, interventions, frameworks, and/or policies.
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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 | 0.102 | 0.119 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.122 | 0.028 |
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".