The intersection of physical activity type and gender in patterns of disordered eating
Bibliographic record
Abstract
Although previous research has linked disordered eating to physical activity involvement, more recent studies suggest that sports participation may be protective against disordered eating; however, due to inconsistent findings on how physical activity affects disordered eating and limited research comparing types of physical activity across weight control behaviours, our aim was to validate physical activity categorization across disordered eating components in both men and women. In this online study, 209 men and 539 women completed questionnaires assessing various components of disordered eating and overall physical activity participation. Pearson correlation coefficients, independent samples t-tests, multiple response crosstabulations, and linear regressions were calculated to achieve the aims of this study. Participation in various types of physical activity significantly predicted various components of disordered eating attitudes, behaviours, and cognitions. Specifically, for women, purging and restricting eating were associated with participation in ball games, while a focus on muscle building was associated with both ball games and weight-class physical activity. For men, body dissatisfaction and excessive exercise were associated with weight-class physical activity participation, while cognitive restraint and muscle building were related to aesthetic sports participation. Purging was associated with both aesthetic and weight-class physical activity, whereas restricting eating was related to weight-class physical activity and ball games. These inconsistencies underscore the need for further research to fully elucidate the relationship between participation in different types of physical activity and the various components of disordered eating.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".