When Guilt Begets Pleasure: The Positive Effect of a Negative Emotion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding how emotions can affect pleasure has important implications both for people and for firms’ communication strategies. Prior research has shown that experienced pleasure often assimilates to the valence of one's active emotions, such that negative emotions decrease pleasure. In contrast, the authors demonstrate that the activation of guilt, a negative emotion, enhances the pleasure experienced from hedonic consumption. The authors show that this effect occurs because of a cognitive association between guilt and pleasure, such that activating guilt can automatically activate cognitions related to pleasure. Furthermore, the authors show that this pattern of results is unique to guilt and cannot be explained by a contrast effect that generalizes to other negative emotions. The article concludes with a discussion of the implications of these findings for marketing and consumption behavior.
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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 | 0.039 | 0.007 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it