First impression formation: Impact of lower anterior facial height in a gender- and ethnicity-diverse photographic model
Bibliographic record
Abstract
Introduction This study investigated whether variations in lower anterior facial height (LAFH) influence the perception of personality traits and attractiveness in frontal facial photographs from a multi-ethnic sample. Methods Standardized photographs of 10 subjects (1 male and 1 female from 5 ethnic groups: Caucasian [white], African American, Asian, Indian, and Hispanic) were selected from the Chicago Face Database (version 3.0). Each image was digitally modified to alter LAFH by ± 3% increments (2-6 mm), producing 5 versions per subject. Each set of 5 images was presented in a random order to a panel of raters, who identified the image best representing 4 traits (intelligence, aggressiveness, friendliness, and confidence) and attractiveness. Analyses used mixed logit regression models and conventional statistics. Results A sample of 133 adults participated. LAFH alterations significantly affected perceived personality traits and attractiveness: the unaltered LAFH images were most frequently selected as the most intelligent, confident, and attractive, whereas increased LAFH (6 mm) were associated with greater perceived aggressiveness in all female photographs, across all ethnic groups. The gender of the rater did not influence trait selection. Conclusions Changes in LAFH alter the perception of personality traits and attractiveness across ethnicities and genders. These findings underscore the social impact of vertical facial proportions in orthodontics and maxillofacial surgery.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".