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Record W1978955244 · doi:10.1080/07448480009596271

An Exploration of the Drive for Muscularity in Adolescent Boys and Girls

2000· article· en· W1978955244 on OpenAlexaff
Donald R. McCreary, Doris K. Sasse

Bibliographic record

VenueJournal of American College Health · 2000
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsSaskatchewan HealthUniversity of ReginaRegina Qu'Appelle Health Region
Fundersnot available
KeywordsPsychologyAttractivenessPhysical attractivenessDevelopmental psychologyDisordered eatingClinical psychologyEating disorders

Abstract

fetched live from OpenAlex

Much of the existing research on disordered eating has centered on the drive for thinness, which is most commonly observed in girls and women. The male standard of bodily attractiveness, however, is bigger, bulkier, and more muscular. Are boys and men motivated to be big and muscular in the same way that girls and women are motivated to be thin? The authors constructed a 15-item survey and administered it to 197 adolescents. The findings showed that the drive for muscularity measure displayed good reliability; that individuals high in the drive were more likely to be boys who were trying to gain both weight and muscle mass; that the drive was related to poor self-esteem and higher levels of depression among boys, but not among girls; and that the drive for muscularity was relatively unrelated to the drive for thinness.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.379
Teacher spread0.335 · 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

Citations1,163
Published2000
Admission routes1
Has abstractyes

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