Visual attention to members of own and other groups: Preferences, determinants, and consequences
Bibliographic record
Abstract
Abstract Many current and past theories of social categorization acknowledge and even underline the critical role that visual processing plays in intergroup misperceptions and biases, yet research that directly measures or manipulates these processes is limited. In the present paper, we reviewed the current literature on visual attention to own and other group faces. First, we explored the development of preferential attention in face processing. Next, we examined these processes in adults and show different patterns of attention for own and other group faces. Although we briefly consider cross‐cultural variations, the focus of this review is on within‐culture differences in visual attention. In particular, we explore preferential attention to specific features on own versus other group faces and to their overall faces. We also discuss potential determinants for differential attention such as experience, threat, individuation and a desire to know in‐groups, and liking. Finally, we explore the implications of differential attention to own and other groups. These consequences range from reduced recognition of other group faces, to impaired identification of emotional expressions, to impeded interaction intentions, and to increased discrimination. Together our analyses provide strong evidence for differences in attention to the faces and eyes of own versus other group members and their role in intergroup biases.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".