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Record W1956863201 · doi:10.1002/per.1844

Processing of Unjust and Just Information: Interpretation and Memory Performance Related to Dispositional Victim Sensitivity

2012· article· en· W1956863201 on OpenAlexaff
Anna Baumert, Kathleen Otto, Nadine Thomas, D. Ramona Bobocel, Manfred Schmitt

Bibliographic record

VenueEuropean Journal of Personality · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Waterloo
FundersDeutsche Forschungsgemeinschaft
KeywordsPsychologyInjusticeConnotationEconomic JusticeSocial psychologyStyle (visual arts)Information processingResolution (logic)Interpretation (philosophy)Sensitivity (control systems)Cognitive psychologyArtificial intelligenceLawComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

With two studies, we tested whether dispositional victim sensitivity involves one of two kinds of biased processing style: either a processing style in which unjust—but not just—information is processed more readily and accurately than neutral information or a processing style in which unjust and just information is processed preferentially over neutral information. In Study 1, victim sensitivity increased the speed with which participants resolved ambiguous sentence fragments in cases in which the resolution yielded an unjust connotation, as well as in cases in which the resolution yielded a just connotation, but not when the resolution was neutral with respect to justice. In Study 2, persons high in victim sensitivity displayed enhanced memory performance for both unjust and just information relative to neutral information over a 1–week retention interval. The results are consistent with the assumption that victim sensitivity is characterized by the activation potential and elaboration of both injustice and justice concepts. Our findings are important for the understanding of how the fear of being exploited among victim–sensitive persons shapes antisocial behaviour. 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 score0.895
Threshold uncertainty score0.199

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.307
Teacher spread0.286 · 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

Citations27
Published2012
Admission routes1
Has abstractyes

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