The perfectionism model of binge eating: Tests of an integrative model.
Bibliographic record
Abstract
This study proposes, tests, and supports the perfectionism model of binge eating (PMOBE), a model aimed at explaining why perfectionism is related to binge eating. According to this model, socially prescribed perfectionism (SPP) confers risk for binge eating by generating exposure to 4 triggers of binge episodes: interpersonal discrepancies, low interpersonal esteem, depressive affect, and dietary restraint. In testing the PMOBE, a daily diary was completed by 566 women for 7 days. Predictions derived from the PMOBE were supported, with tests of mediation suggesting that the indirect effect of SPP on binge eating through triggers of binge episodes was significant. Reciprocal relations were also observed, with certain triggers of binge episodes predicting binge eating (and vice versa). Results supported the incremental validity of the PMOBE over and above self-oriented perfectionism and neuroticism and the generalizability of this model across Asian and European Canadian participants. The PMOBE offers a novel view of individuals with high levels of SPP as active agents who raise their risk of binge eating by generating conditions in their daily lives that are conducive to binge episodes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".