MétaCan
Menu
Back to cohort
Record W2042485602 · doi:10.1002/eat.1026

Weight‐related and shape‐related self‐evaluation in eating‐disordered and non–eating‐disordered women

2001· article· en· W2042485602 on OpenAlexaff
Traci McFarlane, Randi E. McCabe, Josée L. Jarry, Marion P. Olmsted, Janet Polivy

Bibliographic record

VenueInternational Journal of Eating Disorders · 2001
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsDisordered eatingPsychologyAnorexia nervosaBulimia nervosaEating disordersClinical psychologyBody weightDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Weight- and shape-related self-evaluation refers to the process whereby an individual determines her self-worth based on an evaluation of her body weight and shape. This is a hallmark feature of both anorexia and bulimia nervosa, as specified in the 4th ed. of the Diagnostic and Statistical Manual of Mental Disorders. The purpose of this study was to further our understanding of weight-related self-evaluation in eating-disordered women. METHOD: Eating-disordered patients, restrained eaters, and unrestrained eaters completed an experimenter-designed questionnaire that examines different dimensions of weight-related self-evaluation (i.e., the Multidimensional Weight-Related Self-Evaluation Inventory). RESULTS: Results revealed that weight-related self-evaluation is a feature shared, to some extent, by both eating-disordered patients and restrained eaters. However, eating-disordered patients extend weight-related self-evaluation to include more domains of self-esteem than did restrained eaters. DISCUSSION: These findings support a multidimensional approach to weight-related self-evaluation and further our understanding of the process of weight-related self-evaluation in eating-disordered patients.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.306
Teacher spread0.294 · 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.

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

Citations59
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Eating DisordersSame topicEating Disorders and BehaviorsFrench-language works237,207