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Record W4300097579 · doi:10.26443/msurj.v3i1.131

Food temptations spontaneously elicit compensatory beliefs in dieters

2008· article· en· W4300097579 on OpenAlexaffabout
Eva Monson, Bärbel Knaüper, Ilana Knonick

Bibliographic record

VenueMcGill Science Undergraduate Research Journal · 2008
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsMcGill University
Fundersnot available
KeywordsTemptationDietingPsychologySelf-controlSocial psychologyContext (archaeology)Developmental psychologyWeight lossObesityMedicineEndocrinologyBiology

Abstract

fetched live from OpenAlex


 
 
 
 Through various self-regulatory strategies, individuals attempt to strike a balance between the satisfaction of immediate desires and fulfillment of long term goals. One such strategy is described by the compensatory beliefs model, which suggests that individuals rationalize their surrender to an immediate desire or temptation. This model is indirectly supported by earlier studies where compensatory beliefs were induced by the experimental context. The current pilot study examines whether compensatory beliefs can be self-initiated i.e. are spontaneously generated as a response to temptation. We recruited ten female McGill students currently on a weight loss diet and assigned them randomly to a temptation and a control group. We presented all participants with a choice between two identical cookies, differently described for the temptation and control groups: for the temptation condition one cookie was labeled as high in fat and sugar and the other as low in fat and sugar while for the control condition both cookies were labeled as low in fat and sugar. Participants listed compensatory thoughts in both a closed and an open response format. Our pilot data show that dieters indeed spontaneously generate compensatory beliefs in response to temptation. Compensatory beliefs should be considered a factor in unsuccessful self-regulation and more specifically in failed dieting attempts.
 
 
 

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.222
GPT teacher head0.465
Teacher spread0.243 · 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

Citations6
Published2008
Admission routes2
Has abstractyes

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