Bibliographic record
Abstract
In seven studies of naturally occurring, "real-world" emotional events, people demonstrated an immediacy bias in social-emotional comparisons, perceiving their own current or recent emotional reactions as more intense compared with others' emotional reactions to the same events. The events examined include crossing a scary bridge (study 1a), a national tragedy (study 1b), terrorist attacks (studies 2a and 3b), a natural disaster (study 2b), and a presidential election (study 3b). These perceived differences between one's own and others' emotions declined over time, as relatively immediate and recent emotions subsided, a pattern that people were not intuitively aware of (study 2c). This immediacy bias in social-emotional comparisons emerged for both explicit comparisons (studies 1a, 1b, and 3b), and for absolute judgments of emotional intensity (studies 2a, 2b, and 3a). Finally, the immediacy bias in social-emotional comparisons was reduced when people were reminded that emotional display norms might lead others' appearances to understate emotional intensity (studies 3a and 3b). Implications of these findings for social-emotional phenomena are discussed.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".