The influence of lower face vertical proportion on facial attractiveness
Why this work is in the frame
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Bibliographic record
Abstract
This study investigated the influence of changing lower face vertical proportion on the attractiveness ratings scored by lay people.Ninety-two social science students rated the attractiveness of a series of silhouettes with normal, reduced or increased lower face proportions. The random sequences of 10 images included an image with the Eastman normal lower face height relative to total face height [lower anterior face height/total anterior face height (LAFH/TAFH) of 55 per cent], and images with LAFH/TAFH increased or decreased by up to four standard deviations (SD) from the Eastman norm. All the images had a skeletal Class I antero-posterior (AP) relationship. A duplicate image in each sequence assessed repeatability. The participants scored each image using a 10 point numerical scale and also indicated whether they would seek treatment if the image was their own profile. The profile image with normal vertical facial proportions was rated by the lay people as the most attractive. Attractiveness scores reduced as the vertical facial proportions diverged from the normal value. Images with a reduced lower face proportion were rated as significantly more attractive than the corresponding images with an increased lower face proportion. Images with a reduced lower face proportion were also significantly less likely to be judged as needing treatment than the corresponding images with an increased lower face proportion.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it