All the little pointers: a poetic representation of a female elite athlete’s experience of living with and seeking treatment for an eating disorder
Bibliographic record
Abstract
Eating disorders are highly prevalent in elite athletes but the lived experience of these has not been investigated extensively. In this article, we draw on life story data generated from four hours of interviews with a young (20 years plus), Swedish, elite, female athlete in an individual sport, named Lisa (a pseudonym) to explore her experiences of living with, seeking treatment, and attempting to recover from a diagnosed eating disorder. This exploration is accomplished by the use of poetic representations. Having made the methodological case for their use we then present the poems for consideration by the reader. The three poems are entitled All the little pointers, The voice inside my head, and Turning it around. Following this, we offer some reflections on how each poem might act as a pedagogical resource to assist those involved with elite athletes to better understand the nature of eating disorders, how the sporting environment can play a role in initiating and sustaining them, and how athletes might be supported and guided on the road to recovery.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".