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Record W4244262017 · doi:10.31234/osf.io/9tpn7

Fear of Self in Eating Disorders

2020· preprint· en· W4244262017 on OpenAlexafffund
Samantha Wilson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec - Santé
KeywordsConceptualizationConstruct (python library)PsychologyRelevance (law)SelfEating disordersScope (computer science)PsychotherapistClinical psychologyDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Fear of self has been proposed as a transdiagnostic construct, playing a role in not only obsessive compulsive disorder (OCD), but in related disorders as well. In this article, empirical support for the association between eating disorders (EDs) and the fear of self will be reviewed. Support for the fear of self in EDs will be contextualized within the theory of possible selves, self-discrepancy theory, and motivation frameworks. Most of the research that will be presented pertains to a feared overweight self. The relevance of broadening the scope of feared self-domains attributed to EDs beyond weight to include those pertaining to character will be advocated. Furthermore, risk factors theorized to lead to the development and investment in a feared self in OCD are examined and evidence for their applicability to EDs is presented. Treatment strategies targeting self-concept and the fear of self in EDs are also described, highlighting the clinical relevance of integrating this construct into the conceptualization of EDs. Finally, recommendations for future research are proposed.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.029
GPT teacher head0.333
Teacher spread0.304 · 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 designTheoretical or conceptual
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

Citations2
Published2020
Admission routes2
Has abstractyes

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