The role of implicit social bias on holistic processing of out-group faces
Why this work is in the frame
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Bibliographic record
Abstract
Although faces of in-group members are generally thought to be processed holistically, there are mixed findings on whether holistic processing remains robust for faces of out-group members and what factors contribute to holistic processing of out-group faces. This study examined how implicit social bias, experience with out-group members, and ability to process in-group faces holistically might predict the magnitude of holistic processing for faces of two out-groups: other-race and other-age groups. In Experiment 1, Caucasian participants viewed Caucasian (own-race) and East Asian (other-race) faces. In Experiment 2, young adult participants viewed young adult (own-age) and baby (other-age) faces. Each participant completed a composite task with in-group and out-group faces, an implicit association test, and questionnaires about their experience with in-group and out-group members. We found that while the participants had relatively extensive experience with the other-race group, they had limited experience with the other-age group. Nonetheless, implicit social bias was found to positively predict the magnitude of holistic processing for both other-race and other-age faces. Exploratory analyses on the interactions among the predictors suggest that the effect of implicit social bias was primarily observed in participants with strong holistic processing ability of in-group faces but with low level of experience with members of the out-groups. These findings suggest that observers utilize different kinds of information when processing out-group faces, and that social features, such as race or age, are incorporated to influence how out-group faces are processed efficiently.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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