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Record W2552043112 · doi:10.1177/1363459316674788

Treating the binge or the (fat) body? Representations of fatness in a gold standard psychological treatment manual for binge eating disorder

2016· article· en· W2552043112 on OpenAlexaff
Amy Brown‐Bowers, Ashley K. Ward, Nicole Cormier

Bibliographic record

VenueHealth An Interdisciplinary Journal for the Social Study of Health Illness and Medicine · 2016
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsToronto Metropolitan University
FundersBritish Psychological Society
KeywordsBinge eatingBinge-eating disorderGold standard (test)PsychologyClinical psychologyBinge drinkingPsychiatryPsychotherapistMedicineEating disordersBulimia nervosaInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

This article reports the results of a Foucauldian-informed discourse analysis exploring representations of fatness embedded within an empirically based psychological treatment manual for binge eating disorder, a condition characterized by overvaluation of weight and shape. Analyses indicate that the manual prioritizes weight loss with relatively less emphasis placed on treating the diagnostic symptoms and underlying mechanisms of binge eating disorder. We raise critical concerns about these observations and link our findings to mainstream psychology's adoption of the medical framing of fatness as obesity within the "gold standard" approach to intervention. We recommend that psychology as a discipline abandons the weight loss imperative associated with binge eating disorder and fat bodies. We recommend that practitioners locate the problem of fat shame in society as opposed to the individual person's body and provide individuals with tools to identify and resist fat stigma and oppression, rather than provide them with tools to reshape their bodies.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0200.000
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 head0.169
GPT teacher head0.593
Teacher spread0.424 · 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 designQualitative
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

Citations17
Published2016
Admission routes1
Has abstractyes

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