Fantasies of Revenge: An Evolutionary and Individual Differences Account
Bibliographic record
Abstract
In this study, we examine the descriptive qualities of revenge fantasies and test evolutionary and individual-difference accounts for the experience of them. Participants recalled and described a revenge fantasy, and rated its recency, duration, intensity, and the frequency with which they fantasized about revenge overall. They also completed measures of narcissistic entitlement and vengefulness. Consistent with an evolutionary approach to understanding revenge, the results show that men were twice as likely to report fantasies of direct/overt acts of revenge than were women. Vengefulness and narcissistic entitlement did not relate to whether the fantasized revenge act was direct/overt or indirect/covert, but related to the frequency and intensity of participants’ revenge fantasies and the affective experiences participants reported while thinking of them. The findings add specificity to the three-phase model of revenge ( Yoshimura & Boon, 2018 ), and reveal areas of potential growth in research on revenge, in general, and revenge fantasies specifically.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".