Future considerations in research on eating disorders. The Counseling Psychologist
Bibliographic record
Abstract
In the last quarter of the 20th century, the research on eating disorders surged and anorexia and bulimia became household words. These serious disorders were the butt of jokes, the fodder for inappropriate advertising, and, for some, even convoluted status symbols. Inpatient clinics, residential treat-ment centers, and outpatient programs sprang into existence throughout the country, offering expertise and hope for those patients whose needs sur-passed what could be provided to them on an outpatient basis. By the end of the century, the treatment options and the number of available and knowl-edgeable practitioners was certainly better than in the early 1980s, but as the articles in this special issue demonstrate, much remains to be learned about etiology, assessment, and treatment, much less prevention. And despite the field’s acknowledgment that anorexia nervosa and bulimia nervosa are not truly the “golden girl’s ” disease but may increasingly be becoming an equal opportunity disorder, the field has little information on diverse populations to expand our understanding of etiology, assessment, and treatment of these
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.191 | 0.153 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.009 | 0.032 |
| Scholarly communication | 0.016 | 0.041 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.027 | 0.022 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".