The Influence of Averageness on Adults’ Perceptions of Attractiveness: The Effect of Early Visual Deprivation
Bibliographic record
Abstract
Adults who missed early visual input because of congenital cataracts later have deficits in many aspects of face processing. Here we investigated whether they make normal judgments of facial attractiveness. In particular, we studied whether their perceptions are affected normally by a face's proximity to the population mean, as is true of typically developing adults, who find average faces to be more attractive than most other faces. We compared the judgments of facial attractiveness of 12 cataract-reversal patients to norms established from 36 adults with normal vision. Participants viewed pairs of adult male and adult female faces that had been transformed 50% toward and 50% away from their respective group averages, and selected which face was more attractive. Averageness influenced patients' judgments of attractiveness, but to a lesser extent than controls. The results suggest that cataract-reversal patients are able to develop a system for representing faces with a privileged position for an average face, consistent with evidence from identity aftereffects. However, early visual experience is necessary to set up the neural architecture necessary for averageness to influence perceptions of attractiveness with its normal potency.
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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 | 0.002 |
| 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) | 0.001 | 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 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".