Dress is a Fundamental Component of Person Perception
Why this work is in the frame
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Bibliographic record
Abstract
ACADEMIC ABSTRACT: Clothing, hairstyle, makeup, and accessories influence first impressions. However, target dress is notably absent from current theories and models of person perception. We discuss three reasons for this minimal attention to dress in person perception: high theoretical complexity, incompatibility with traditional methodology, and underappreciation by the groups who have historically guided research in person perception. We propose a working model of person perception that incorporates target dress alongside target face, target body, context, and perceiver characteristics. Then, we identify four types of inferences for which perceivers rely on target dress: social categories, cognitive states, status, and aesthetics. For each of these, we review relevant work in social cognition, integrate this work with existing dress research, and propose future directions. Finally, we identify and offer solutions to the theoretical and methodological challenges accompanying the psychological study of dress. PUBLIC ABSTRACT: Why is it that people often agonize over what to wear for a job interview, a first date, or a party? The answer is simple: They understand that others' first impressions of them rely on their clothing, hairstyle, makeup, and accessories. Many people might be surprised, then, to learn that psychologists' theories about how people form first impressions of others have little to say about how people dress. This is true in part because the meaning of clothing is so complex and culturally dependent. We propose a working model of first impressions that identifies four types of information that people infer from dress: people's social identities, mental states, status, and aesthetic tastes. For each of these, we review existing research on clothing, integrate this research with related work from social psychology more broadly, and propose future directions for research.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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