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Record W2148815191 · doi:10.1111/jabr.12032

Use Your Imagination: College Women's Responses to a Social‐Evaluative Body Image Threat

2015· article· en· W2148815191 on OpenAlexafffund
Larkin Lamarche, K. Alysse Bailey, Kimberley L. Gammage

Bibliographic record

VenueJournal of Applied Biobehavioral Research · 2015
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyShameAnxietySocial anxietySocial psychologyHeart rateDevelopmental psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

This study examined psychological and heart rate responses to an imagined social‐evaluative body image threat in women (N = 97). Participants were randomly assigned to picture themselves trying on swimsuits in a store with a group of friends (social‐evaluative threat) or alone (non‐social‐evaluative threat). Measures of state body image and heart rate recordings were completed prior to and following the scenario. A significant group‐by‐time interaction was found for state body image, F(2, 93) = 3.69, p = .03, with the highest body shame and social physique anxiety reported in the social‐evaluative group. No differences were found for heart rate. The findings highlight the usefulness of imagined scenarios when examining psychological responses and the challenges of capturing changes in physiological outcomes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.292
GPT teacher head0.520
Teacher spread0.229 · 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 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

Citations8
Published2015
Admission routes2
Has abstractyes

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