Disordered Eating in High School Dance Students: Some Practical Considerations
Bibliographic record
Abstract
For a quarter of a century performing arts medicine personnel have been aware of the elevated risk of eating disorders in preprofessional high school dance students. This article reviews the etiological considerations related to this trend and how they affect the prevention and management of eating disorders. Are the students in question making a considered response to society's demand for a lean appearance, or do they represent a sub-population that is suffering from clinical disorders (the pathologic results of dieting behaviors, self-image problems, social difficulties, physical injuries, and so forth)? Recent school-based programs have shown encouraging results in reducing incidence. On the basis of what those programs have taught us, practical recommendations for the management of existing disorders are presented, from a psychiatric perspective.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.015 | 0.009 |
| 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".