Cultural influences on face scanning are consistent across infancy and adulthood
Bibliographic record
Abstract
The emergence of cultural differences in face scanning is thought to be shaped by social experience. However, previous studies mainly investigated eye movements of adults and little is known about early development. The current study recorded eye movements of British and Japanese infants (aged 10 and 16 months) and adults, who were presented with static and dynamic faces on screen. Cultural differences were observed across all age groups, with British participants exhibiting more mouth scanning, and Japanese individuals showing increased central face (nose) scanning for dynamic stimuli. Age-related influences independent of culture were also revealed, with a shift from eye to mouth scanning between 10 and 16 months, while adults distributed their gaze more flexibly. Against our prediction, no age-related increases in cultural differences were observed, suggesting the possibility that cultural differences are largely manifest by 10 months of age. Overall, the findings suggest that individuals adopt visual strategies in line with their cultural background from early in infancy, pointing to the development of a highly adaptive face processing system that is shaped by early sociocultural experience.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".