Workforce Diversity in Eating Disorders: A Multi-Methods Study
Bibliographic record
Abstract
Despite growing recognition of the importance of workforce diversity in health care, limited research has explored diversity among eating disorder (ED) professionals globally. This multi-methods study examined diversity across demographic and professional variables. Participants were recruited from ED and discipline-specific professional organizations. Participants' (n = 512) mean age was 41.1 years (SD = 12.5); 89.6% (n=459) of participants identified as women, 84.1% (n = 419) as heterosexual/straight, and 73.0% (n = 365) as White. Mean years working in EDs was 10.7 years (SD = 9.2). Qualitative analysis revealed three themes resulting in a theoretical framework to address barriers to increasing diversity. Perceived barriers were the following: "stigma, bias, stereotypes, myths"; "field of eating disorders pipeline"; and "homogeneity of the existing field." Findings suggest limited workforce diversity within and across nations. The theoretical model suggests a need for focused attention to the educational pipeline, workforce homogeneity, and false assumptions about EDs, and it should be tested to evaluate its utility within the EDs field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".