Face Race Processing and Racial Bias in Early Development: A Perceptual-Social Linkage
Bibliographic record
Abstract
Infants have asymmetrical exposure to different types of faces (e.g., more human than other-species, more female than male, and more own-race than other-race). What are the developmental consequences of such experiential asymmetry? Here we review recent advances in research on the development of cross-race face processing. The evidence suggests that greater exposure to own- than other-race faces in infancy leads to developmentally early perceptual differences in visual preference, recognition, category formation, and scanning of own- and other-race faces. Further, such perceptual differences in infancy may be associated with the emergence of implicit racial bias, consistent with a Perceptual-Social Linkage Hypothesis. Current and future work derived from this hypothesis may lay an important empirical foundation for the development of intervention programs to combat the early occurrence of implicit racial bias.
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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 | 0.002 | 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 | 0.004 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".