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 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 | 0.002 | 0.021 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".