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Record W3040325737 · doi:10.1111/spc3.12554

Revenge as social interaction: Merging social psychological and interpersonal communication approaches to the study of vengeful behavior

2020· article· en· W3040325737 on OpenAlex
Susan D. Boon, Stephen M. Yoshimura

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.

Bibliographic record

VenueSocial and Personality Psychology Compass · 2020
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConceptualizationInterpersonal communicationPsychologyPerspective (graphical)Social exchange theorySocial psychologySocial relationInterpersonal interactionProcess (computing)Interpersonal relationshipCognitive scienceEpistemologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The purpose of this essay is to review and assess the benefits of merging social psychological and communication theory‐based approaches to the study of vengeful behavior in interpersonal interactions. We first outline the parallel but complementary perspectives that each discipline takes to the conceptualization of revenge. From there, we identify some of the core features that would be present in an integrated approach that conceptualizes revenge as an interpersonal process (i.e., an interaction or exchange), and then highlight new directions for both inquiry and theory building that an integrative approach reveals as worthy of scholarly pursuit. We argue that conceptualizing and studying revenge in ways that blend both social psychological and communication‐based views offers numerous opportunities to examine the dynamics between a provoking party and an avenger, and provides a richer and more insightful theoretical understanding of vengeful behavior than either perspective could offer alone.

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)0.001
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 score0.795
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.353
GPT teacher head0.437
Teacher spread0.084 · 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