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Record W1926069453 · doi:10.1002/ejsp.807

Predicting alternative strategies for preserving a belief in a just world: The case of repressive coping style

2011· article· en· W1926069453 on OpenAlexaff
Carolyn L. Hafer

Bibliographic record

VenueEuropean Journal of Social Psychology · 2011
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsBrock University
Fundersnot available
KeywordsJust-world hypothesisPsychologySocial psychologyCoping (psychology)Style (visual arts)Clinical psychologyHistory

Abstract

fetched live from OpenAlex

Abstract Researchers suggest that observers of innocent suffering will negatively evaluate the victim as a strategy for maintaining their belief in a just world. We propose an alternative class of strategies and test whether individual differences in repressive coping style predict the type of strategy people will use. In the first two studies, we exposed repressors versus nonrepressors to victims whose suffering should pose a high versus low threat to the need to believe in a just world. Repressors had a greater tendency to positively reappraise the high threat victim's suffering. Nonrepressors had a greater tendency to negatively evaluate the high threat victim. A third study replicated the results for the high threat conditions and suggested that repressors' positive reappraisal is not because of a tendency to minimize suffering. Our research (i) demonstrates a class of strategies for preserving the belief in a just world other than negatively evaluating the victim and (ii) is among the first to examine directly an individual difference predictor of alternative just‐world preservation strategies. Copyright © 2011 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)0.001
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 score0.624
Threshold uncertainty score0.339

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.246
GPT teacher head0.379
Teacher spread0.133 · 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

Citations39
Published2011
Admission routes1
Has abstractyes

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