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Record W2005377796 · doi:10.1002/ejsp.97

Asymmetrical impact: vigilance for differences and self‐relevant stimuli

2002· article· en· W2005377796 on OpenAlexaff
James M. Olson, Leslie M. Janes

Bibliographic record

VenueEuropean Journal of Social Psychology · 2002
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyAffect (linguistics)Vigilance (psychology)Social psychologyDevelopmental psychologyCognitive psychologyCommunication

Abstract

fetched live from OpenAlex

Abstract We hypothesized that people are ‘vigilant’ for differences between stimuli. In particular, we compared the reactions elicited by unexpected differences versus unexpected similarities. Participants imagined themselves in several situations where they learned something unexpected. This unexpected information showed either that two things previously thought to be similar were actually different or that two things previously thought to be different were actually similar. Also, the new information was either beneficial, neutral, or detrimental to the perceiver. Participants indicated for each situation how surprised they would be and how they would feel. Unexpected differences were rated as more surprising than unexpected similarities for positive and negative events, though not for neutral events. Participants also reported that beneficial differences would produce more positive affect than beneficial similarities, whereas detrimental differences would produce more negative affect than detrimental similarities. These findings support the asymmetrical impact hypothesis that differences have more psychological impact than similarities. Copyright © 2002 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)0.000
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 score0.910
Threshold uncertainty score0.443

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 studies0.0000.000
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 head0.175
GPT teacher head0.354
Teacher spread0.179 · 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

Citations10
Published2002
Admission routes1
Has abstractyes

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