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Not just a pretty face: Physical attractiveness and perfectionism in the risk for eating disorders

2000· article· en· W1965797814 on OpenAlexaff
Caroline A. Davis, Gordon Claridge, John Fox

Bibliographic record

VenueInternational Journal of Eating Disorders · 2000
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsMcMaster UniversityYork UniversityUniversity of TorontoToronto General Hospital
Fundersnot available
KeywordsPhysical attractivenessPerfectionism (psychology)PsychologyAttractivenessDisordered eatingNeuroticismBeautyContext (archaeology)PersonalityHuman physical appearanceEating disordersDevelopmental psychologyBig Five personality traitsClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Considerable research has examined the correlates and consequences of both objective and subjective ratings of physical attractiveness. Numerous studies have found, for example, that subjective physical attractiveness is inversely related to weight and diet concerns. Surprisingly, however, no research has examined the relationship between objective physical beauty and eating pathologies, despite clinical and theoretical reasons to expect a positive relationship between the two. METHOD: We rated 203 young women on facial attractiveness and obtained self-report measures of perfectionism, neuroticism, and weight preoccupation. RESULTS: Attractiveness was positively related to weight preoccupation after controlling for body size and neurotic perfectionism. DISCUSSION: These findings provide the first evidence of physical beauty as a risk for disordered eating, and confirm earlier evidence that the relationship between general perfectionism and disordered eating only occurs when combined with a tendency to be anxious and hypercritical. Results are discussed in the context of identity formation and the attractiveness stereotype.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.349
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations64
Published2000
Admission routes1
Has abstractyes

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