Examining the relationship between muscularity attitude and personal trainer preference
Bibliographic record
Abstract
Given the impact of current body image ideals (fit and lean/muscular) and the widespread attention associated with the obesity epidemic, health club memberships and the demand for personal training services have soared (IHRSA, 2012). The primary purpose of the current study was to examine whether the physique of a personal trainer influenced a participant's choice when self-selecting a same gendered personal trainer. A secondary purpose examined whether the choice of personal trainer was influenced by one's muscularity attitude. Participants (N = 805) completed the attitudinal subscale of the Drive for Muscularity Scale (McCreary &Sasse, 2000) and were asked to rank four silhouette contour drawings of personal trainers (same gender) of varying muscular appearances (underweight, lean/muscular, hypermuscular, and overweight). The results indicated that both male and female participants preferred the trainer with a lean/muscular physique compared to the other three physiques. A one-way ANOVA revealed statistically significant differences in muscularity attitude and personal trainer choice among men (p
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".