Gender differences in foot shape: a study of Chinese young adults
Bibliographic record
Abstract
One important extrinsic factor that causes foot deformity and pain in women is footwear. Women's sports shoes are designed as smaller versions of men's shoes. Based on this, the current study aims to identify foot shape in 1,236 Chinese young adult men and 1,085 Chinese young adult women. Three-dimensional foot shape data were collected through video filming. Nineteen foot shape variables were measured, including girth (4 variables), length (4 variables), width (3 variables), height (7 variables), and angle (1 variable). A comparison of foot measures within the range of the common foot length (FL) categories indicates that women showed significantly smaller values of foot measures in width, height, and girth than men. Three foot types were classified, and distributions of different foot shapes within the same FL were found between women and men. Foot width, medial ball length, ball angle, and instep height showed significant differences among foot types in the same FL for both genders. There were differences in the foot shape between Chinese young women and men, which should be considered in the design of Chinese young adults' sports shoes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".