Trait Impressions as Overgeneralized Responses to Adaptively Significant Facial Qualities: Evidence from Connectionist Modeling
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Bibliographic record
Abstract
Connectionist modeling experiments tested anomalous-face and baby-face overgeneralization hypotheses proposed to explain consensual trait impressions of faces. Activation of a neural network unit trained to respond to anomalous faces predicted impressions of normal adult faces varying in attractiveness as well as several elderly stereotypes. Activation of a neural network unit trained to respond to babies' faces predicted impressions of adults varying in babyfaceness as well as 1 elderly stereotype. Thus, similarities of normal adult faces to anomalous faces or babies' faces contribute to impressions of them quite apart from knowledge of overlapping social stereotypes. The evolutionary importance of appropriate responses to unfit individuals or babies is presumed to produce a strong response preparedness that is overgeneralized to faces resembling the unfit or babies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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