Self‐oriented and socially prescribed perfectionism in the Eating Disorder Inventory Perfectionism subscale
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to demonstrate the existence and the importance of the distinction between self-oriented and socially prescribed perfectionism in the Eating Disorder Inventory Perfectionism subscale (EDI-P). METHOD: Trait perfectionism, measured by the EDI-P, and eating disorder symptoms, measured by the 26-item Eating Attitudes Test, were examined in 220 university students (110 women and 110 men) belonging to a campus-based fitness facility. RESULTS: Confirmatory factor analysis indicated that, for both genders, the EDI-P is best represented by a multidimensional factor structure with three self-oriented perfectionism items (EDI-SOP) and three socially prescribed perfectionism items (EDI-SPP). Structural equation modeling demonstrated that, for both genders, EDI-SOP and EDI-SPP are related independently to eating disorder symptoms. Moderational analysis indicated that, for women, the impact of EDI-SOP on eating disorder symptoms is dependent on the level of EDI-SPP. DISCUSSION: It is suggested that future research should acknowledge the empirical and theoretical implications of having EDI-SOP and EDI-SPP in the EDI-P. It is cautioned that EDI-SOP and EDI-SPP are a partial representation of an already published multidimensional model of trait perfectionism.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".