Can perceptual expertise accountfor the own-race bias in face recognition? A split-brain study
Why this work is in the frame
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Bibliographic record
Abstract
The own-race bias (ORB) in facial recognition is characterised by increased accuracy in recognition of individuals from one's own racial group, relative to individuals from other racial groups. Here we report data from a split-brain patient indicating that the ORB may be tied to functions lateralised in the right cerebral hemisphere. Patient JW (a Caucasian) performed a delayed match-to-sample task for faces that varied both the race of the facial memoranda-Caucasian or Japanese-and the cerebral hemisphere performing the task. While JW's left hemisphere showed no effect of race on facial recognition, his right hemisphere demonstrated a significant performance advantage for Caucasian faces. These findings are discussed in relation to stimulus familiarity and the development of perceptual expertise.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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