What’s in a gaze, what’s in a face?: The direct gaze effect can be modulated by emotion expression.
Bibliographic record
Abstract
Gaze direction and emotion expression are salient facial features that facilitate social interactions. Previous studies addressed how gaze direction influences the evaluation and recognition of emotion expressions, but few have tested how emotion expression influences attentional processing of direct versus averted gaze faces. The present study examined whether the prioritization of direct gaze (toward the observer) relative to averted gaze (away from the observer) is modulated by the emotional expression of the observed face. Participants identified targets presented on the forehead of one of four faces in a 2 × 2 design (gaze direction: direct/averted; motion: sudden/static). Emotion expressions of the faces (neutral, angry, fearful, happy, disgusted) differed across participants. Direct gaze effects emerged-response times were shorter for targets on direct gaze than on averted gaze faces. This direct gaze effect was enhanced in angry faces (approach-oriented) and reduced in fearful faces (avoidance-oriented). "Weaker" approach- and avoidance-oriented expressions (happy and disgusted) did not modulate the direct gaze effect. These findings suggest that the context of facial emotion expressions influences attentional processing. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".