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Record W1902133826 · doi:10.1002/ejsp.1874

Vertical individualism and injustice: The self‐restorative function of revenge

2012· article· en· W1902133826 on OpenAlexafffund
Agnes Zdaniuk, D. Ramona Bobocel

Bibliographic record

VenueEuropean Journal of Social Psychology · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of WaterlooUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInjusticeIndividualismSocial psychologyPsychologyOrganizational justiceEconomic JusticeIdentity (music)Interpersonal communicationSocial identity theoryOrganizational commitmentSocial groupPolitical scienceAesthetics

Abstract

fetched live from OpenAlex

Abstract In the current paper, we examine the role of vertical individualism in determining revenge behavior following an injustice. Drawing on existing theory and research, we hypothesized that victims who are more vertically individualistic will be more likely than those who are less vertically individualistic to engage in revenge following the experience of injustice as a means of restoring self‐esteem. The results from three studies—employing different methodologies and operationalizations of revenge—support our reasoning. Moreover, two of the studies provide support for the proposed self‐esteem maintenance mechanism underlying the relation between vertical individualism and revenge. Although much research in psychology and organizational justice has demonstrated that the experience of injustice can threaten one's identity, our data are the first to demonstrate that responding to injustice can restore people's self‐esteem to homeostasis. The present studies thus demonstrate that in some instances revenge may have an intrapsychic benefit for the victim, which helps to explain why some people engage in revenge despite possible negative interpersonal consequences. We discuss implications of our findings for social and organizational justice theory and for potentially mitigating revenge reactions to injustice. Copyright © 2012 John Wiley & Sons, Ltd.

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.

How this classification was reachedexpand

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)0.003
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 score0.748
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.000
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 head0.057
GPT teacher head0.381
Teacher spread0.323 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations41
Published2012
Admission routes2
Has abstractyes

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