Self-monitoring hinders the ability to read affective facial expressions
Why this work is in the frame
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Bibliographic record
Abstract
People frequently regulate their own behaviour in an effort to be socially appropriate. Here we ask how self-monitoring influences our accuracy when reading others’ facial expressions. We used webcams and pre-programmed conversations to induce self-monitoring or other-monitoring in participants, before they classified the affective facial expressions of video-recorded actors. Two experiments showed that self-monitoring reduces sensitivity to affective facial expression in others. Experiment 1 showed that self-monitoring participants were less sensitive to emotional facial expressions than other-monitoring and neutral condition participants. Experiment 2 found the same result, but only in participants who rated the pre-programmed conversations as high in believability. We discuss possible mechanisms by which this may occur, including the role of social stress, divided attention, and automatic latent imitation when processing others’ facial expressions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 0.003 |
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