Sex Differences in Relative Foot Length and Perceived Attractiveness of Female Feet: Relationships among Anthropometry, Physique, and Preference Ratings
Bibliographic record
Abstract
Foot size proportionate to stature is smaller in women than in men, and small feet apparently contribute to perceived physical attractiveness of females. This exploratory study investigated the sex difference in relative foot length and interrelations among foot length, physique, and foot preference ratings in samples from Austria and Canada, each comprised of 75 men and 75 women. The findings included the following lines of evidence: the sex difference in relative foot length replicated in both data sets; the magnitude of this sex effect was large. Relative foot length was smaller in young, nulliparous, and slim women. Pointed-toe and high-heel shoes were more likely worn by smaller, lighter, and slimmer women. Men reported liking women's feet in general more than vice versa. A vast majority of both men and women favored small feet in women, but large feet in men. One's own foot size appeared to correspond to evaluations of attractiveness; particularly, women with small feet preferred small feet in women in general. The preference for small feet in women was convergent across different methods of evaluating attractiveness. Directions for investigations in this emerging field of research on physical attractiveness are discussed.
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 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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".