Perceiver and target characteristics contribute to impression formation differently across race and gender.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social impressions arise from characteristics of both perceivers and targets. However, empirical research in the domain of impression formation has yet to quantify the extent to which perceiver and target characteristics uniquely contribute to impressions across group boundaries (e.g., race, gender). To what extent does an impression arise from "our mind" versus "a target's face", and does this process differ for impressions across race and gender? We explored this question by estimating intraclass correlation coefficients (ICCs) from cross-classified multilevel models of 188,472 face ratings from 2,230 participants (Study 1) and 219,658 ratings from 2,984 participants (Study 2). We partitioned the total variance in ratings on a trait dimension (trustworthiness, dominance, youthful/attractiveness) into variance explained by perceivers versus targets, and compared these ICCs among different groups (e.g., ratings of own- vs. other-group targets). Overarching results reveal (a) target appearance matters more for women than men, (b) target appearance matters more for impressions on youthful/attractiveness than trustworthiness or dominance dimensions, (c) differences in perceiver/target influences across race did not consistently replicate, and (d) these differences are absent in minimal groups, supporting the role of racial and gender stereotypes in driving these effects. Overall, perceiver characteristics contribute more to impressions than target appearance. Our findings disentangle the contributions of perceiver and targets to impressions and illustrate that the process of impression formation is not equal across various group boundaries. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 it