Elasticity of emotions to multiple interpersonal transgressions.
Bibliographic record
Abstract
After an interpersonal mishap-like blowing off plans with a friend, forgetting a spouse's birthday, or falling behind on a group project-wrongdoers typically feel guilty for their misbehavior, and victims feel angry. These emotions are believed to possess reparative functions; their expression prevents future mistakes from reiterating. However, little research has examined people's emotional reactions to mistakes that happen more than once. In seven preregistered studies, we assessed wrongdoers' and victims' emotions that arise after one transgression and again after another. Following two (or more) consecutive transgressions, wrongdoers felt guiltier, and victims felt angrier. However, from one transgression to the next, increases to anger were significantly greater than increases to guilt. Likewise, after transgression repair, anger decreased more than guilt did. In short, we found that anger is more elastic than guilt, which suggests a new perspective on emotions: The sensitivity to which emotions update in response to new circumstances. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.002 |
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; both teacher heads agree on what is shown here.
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".