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Record W1982909927 · doi:10.1037/a0029549

Listen to your heart: When false somatic feedback shapes moral behavior.

2012· article· en· W1982909927 on OpenAlexafffund
Jun Gu, Chen‐Bo Zhong, Elizabeth Page‐Gould

Bibliographic record

VenueJournal of Experimental Psychology General · 2012
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHeartbeatPsychologyDeceptionLyingSocial psychologyActive listeningDistressCognitive psychologyCommunicationComputer securityPsychotherapist

Abstract

fetched live from OpenAlex

A pounding heart is a common symptom people experience when confronting moral dilemmas. The authors conducted 4 experiments using a false feedback paradigm to explore whether and when listening to a fast (vs. normal) heartbeat sound shaped ethical behavior. Study 1 found that perceived fast heartbeat increased volunteering for a just cause. Study 2 extended this effect to moral transgressions and showed that perceived fast heartbeat reduced lying for self-gain. Studies 3 and 4 explored the boundary conditions of this effect and found that perceived heartbeat had less influence on deception when people are mindful or approach the decision deliberatively. These findings suggest that the perceived physiological experience of fast heartbeats may signal greater distress in moral situations and hence motivate people to take the moral high road.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.204
GPT teacher head0.393
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations47
Published2012
Admission routes2
Has abstractyes

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