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Record W2079010133 · doi:10.1080/1612197x.2008.9671855

Men's and women's drive for muscularity: Gender differences and cognitive and behavioral correlates

2008· article· en· W2079010133 on OpenAlexaff
Jacob W. Kyrejto, Amber D. Mosewich, Kent C. Kowalski, Diane E. Mack, Peter R.E. Crocker

Bibliographic record

VenueInternational Journal of Sport and Exercise Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of British ColumbiaBrock UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsPsychologyCognitionClinical psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract This study explored gender differences in drive for muscularity (DFM), as well as cognitive and behavioral correlates of DFM. Although men (n = 71) reported a higher DFM than women (n = 126), the difference in DFM disappeared when the emphasis on the form of muscularity shifted from muscle size to muscle tone. Men and women reported a number of similar cognitive and behavioral correlates of DFM. The most commonly reported were physical activity (reported by 74.6% of men and 73.0% of women), diet (33.8% of men, 26.2% of women), cognitive problem solving (32.4% of men, 29.4% of women), leisure activity (21.1% of men, 23.8% of women), and social support (18.3% of men, 23.0% of women). Overall, these results support the relevance of DFM to both men and women and the need to better understand a broad range of cognitive and behavioral correlates of DFM.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.027
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.352
Teacher spread0.314 · 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.

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

Citations42
Published2008
Admission routes1
Has abstractyes

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