Time Course of Cultural Differences in Spatial Frequency Use for Face Identification
Bibliographic record
Abstract
Several previous studies of eye movements have put forward that, during face recognition, Easterners spread their attention across a greater part of their visual field than Westerners. Recently, we found that culture's effect on the perception of faces reaches mechanisms deeper than eye movements, therefore affecting the very nature of information sampled by the visual system: that is, Westerners globally rely more than Easterners on fine-grained visual information (i.e. high spatial frequencies; SFs), whereas Easterners rely more on coarse-grained visual information (i.e. low SFs). These findings suggest that culture influences basic visual processes; however, the temporal onset and dynamics of these culture-specific perceptual differences are still unknown. Here, we investigate the time course of SF use in Western Caucasian (Canadian) and East Asian (Chinese) observers during a face identification task. Firstly, our results confirm that Easterners use relatively lower SFs than Westerners, while the latter use relatively higher SFs. More importantly, our results indicate that these differences arise as early as 34 ms after stimulus onset, and remain stable through time. Our research supports the hypothesis that Westerners and Easterners initially rely on different types of visual information during face processing.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 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".