Individuation training with other‐race faces reduces preschoolers’ implicit racial bias: a link between perceptual and social representation of faces in children
Why this work is in the frame
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Bibliographic record
Abstract
The present study examined whether perceptual individuation training with other-race faces could reduce preschool children's implicit racial bias. We used an 'angry = outgroup' paradigm to measure Chinese children's implicit racial bias against African individuals before and after training. In Experiment 1, children between 4 and 6 years were presented with angry or happy racially ambiguous faces that were morphed between Chinese and African faces. Initially, Chinese children demonstrated implicit racial bias: they categorized happy racially ambiguous faces as own-race (Chinese) and angry racially ambiguous faces as other-race (African). Then, the children participated in a training session where they learned to individuate African faces. Children's implicit racial bias was significantly reduced after training relative to that before training. Experiment 2 used the same procedure as Experiment 1, except that Chinese children were trained with own-race Chinese faces. These children did not display a significant reduction in implicit racial bias. Our results demonstrate that early implicit racial bias can be reduced by presenting children with other-race face individuation training, and support a linkage between perceptual and social representations of face information in children.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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