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The Benefits, Costs, and Paradox of Revenge

2010· article· en· W2097969719 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSocial and Personality Psychology Compass · 2010
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInjusticeAngerHarmPsychologyEconomic JusticeSocial psychologyPerceptionPower (physics)CriminologyLawPolitical science

Abstract

fetched live from OpenAlex

Abstract In this article, we examine the psychology of revenge. We begin by discussing challenges associated with defining revenge. We then review the relative costs and benefits associated with taking revenge. Although revenge can deter future harm, promote cooperation, and restore avengers’ self‐worth and power, it can also contribute to conflict escalation and adverse psychological outcomes for avengers, such as depression and reduced life satisfaction. Next, we examine the prevalence of revenge. In distinguishing between the desire for revenge and act of revenge, we challenge the notion that the act of revenge is an automatic or pervasive response to injustice. We highlight four factors that influence whether victims of injustice choose to take revenge: the persistence of anger, perceptions of the costs of revenge, cultural and religious values regarding revenge, and the presence of external systems that can restore justice on behalf of victims.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.363
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it