Pixies in a windstorm: Tracing Australian gymnasts’ stories of athlete maltreatment through media data
Bibliographic record
Abstract
The media have reported stories of a toxic sport culture in elite gymnastics. Our interdisciplinary research team, through the lens of cultural relativism, sought to present athlete maltreatment as culturally constructed across individual, organizational and national cultural layers in Olympic development contexts. Tracing storied media data from elite Australian gymnasts, we tailored our sociocultural interpretation of athlete maltreatment within an Asia-Pacific context. We engaged in a reflexive thematic analysis to analyze and recognize our interpretations of the media data. We use a polyphonic vignette to highlight multiple storylines of Olympic athlete maltreatment across five temporal phases: (1) defining an Australian gymnast, (2) grooming an Australian gymnast, (3) living as an Australian gymnast, (4) questioning gymnastics and (5) what happens to Australian gymnasts now? Utilizing Asia-Pacific media data facilitated our nuanced interpretation of infacing and outfacing athlete maltreatment as media sources project athlete narratives in alignment with cultural agendas.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".