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Record W2059998814 · doi:10.1080/02699931003593942

Negative emotions can attenuate the influence of beliefs on logical reasoning

2010· article· en· W2059998814 on OpenAlex

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

VenueCognition & Emotion · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologySyllogismContent (measure theory)Affect (linguistics)Consistency (knowledge bases)ScrutinyContrast (vision)Cognitive psychologySocial psychologyLogical reasoningEpistemology

Abstract

fetched live from OpenAlex

Although the influence of beliefs on logical reasoning is well documented, how emotions modulate the effect of beliefs during reasoning remains unexamined. We instructed participants to reason about syllogisms involving neutral or emotionally charged content. We also manipulated the consistency of beliefs with logical validity. When content was neutral, participants exhibited the belief-bias effect observed in previous studies of reasoning. In contrast, when confronted with emotionally charged content participants were less likely to be influenced by their beliefs. Our results suggest that under certain conditions negative emotions can attenuate the influence of beliefs during logical reasoning. Drawing on the affect infusion model, we attribute this effect to a more vigilant, systematic scrutiny of beliefs in the presence of negative emotions.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.099
GPT teacher head0.373
Teacher spread0.274 · 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