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Record W4231587044 · doi:10.32920/ryerson.14650050.v1

An Experimental Investigation of Body Displacement Theory in Restrained Eaters

2021· preprint· en· W4231587044 on OpenAlexaff
Danielle Elizabeth MacDonald

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsFeelingDisplacement (psychology)ShamePsychologyAssociation (psychology)CognitionEating disordersSocial psychologyImplicit-association testClinical psychologyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Body Displacement Theory posits that individuals with eating and weight concerns may mislabel feelings of ineffectiveness as feeling fat. Study 1used a non-clinical sample to create an Implicit Association Test for body image (IAT-BI) to measure implicit body dissatisfaction, as body displacement is thought to be an automatic cognitive/affective process. The IAT-BI was moderately and significantly correlated with explicit measures of body dissatisfaction, body shame, and restrained eating. In Study 2, an experimental manipulation was used to induce ineffectiveness in a non-clinical sample, and effects on implicit and explicit body image and related variables were measured. Contrary to hypotheses, feeling ineffective did not lead to feeling fat in comparison to those in a control condition. These findings may suggest that body displacement was not successfully induced by the manipulation, or that body displacement may be process unique to those with eating disorders. The implications of the study are discussed.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.351
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2021
Admission routes1
Has abstractyes

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