Functional significance of waist-to-hip ratio / by Tanya D. Spencer
Bibliographic record
Abstract
Waist-to-hip ratio (WHR) may be important and highly visible ?honest advertisement? of general and reproductive health and, hence, physical attractiveness. Research shows that men and women aged 18-86 agree on what constitutes attractive WHRs: .7 for women and .9 for men. However, stimuli used in previous studies confound weight with WHR \nbecause the line drawings or photographs are altered to yield a range of WHRs and the actual body mass index (BMI) is not available. The purpose of the present study was to compare the predictive power of WHR and BMI in explaining the variance in attractiveness judgements. Unretouched photographs of men and women that varied by WHR and BMI were rated by men and women on several dimensions (masculine, \nfeminine, good-looking, sexy, intelligent, interested in having children, capable of having children, age, weight, weight category, attractiveness for marriage, attractiveness for brief casual sex) and ranked according to global preference. Results showed that photographs of WHRs of .7 for females and only .8 for males were seen as most attractive. However, \nratings of attractiveness were largely determined by BMI of the person pictured, although WHR was a sole predictor of age estimates and masculinity ratings. People with high BMIs were generally seen as less attractive and less intelligent. Raters, particularly women, were quite accurate at estimating the weight of people pictured. Ratings were \nlargely consistent across rater characteristics, including sex, and ratings (pictures presented in random order one at a time) and rankings (pictures presented in random order simultaneously). Self-report anthropometric measurements were also found to be fairly reliable. These results suggest that BMI, not WHR may be the best predictor of judgements of physical attractiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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; both teacher heads agree on what is shown here.
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".