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Record W4415030829 · doi:10.1002/bdm.70046

All Together Now: Genes, Interpersonal Touch, and Self‐Conscious Processes Jointly Guide Cooperative Behavior

2025· article· en· W4415030829 on OpenAlexaff
Richard P. Bagozzi, Jason Stornelli, Willem Verbeke, Benjamin E. Bagozzi, Avik Chakrabarti, Tiffany Vu

Bibliographic record

VenueJournal of Behavioral Decision Making · 2025
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsEmpathyContext (archaeology)Interpersonal communicationMediationInterpersonal interactionInterpersonal relationshipSocial relationPoint (geometry)

Abstract

fetched live from OpenAlex

ABSTRACT Cooperation and trust are critical parts of many relationships. However, such relationships are often studied in siloed ways, leading to incomplete explanations of behavior (e.g., from the point of view of a buyer or a seller, but not necessarily both). This paper makes three contributions to broadening this perspective. First, the authors develop a model incorporating individual differences (genetics), environmental (interpersonal touch), and psychological (empathy and trust) elements to shed light on when and how cooperation is influenced in dyadic relationships. Empathy was predicted to be elicited by the interaction of human touch and the COMT gene to induce, in turn, felt trust and cooperative behaviors. Second, the centipede game is used as a behaviorally relevant context to study how and under what conditions players cooperate while competing with each other. The results of a conditional serial mediation demonstrate that cooperative responses are guided by the interaction of touch and the COMT gene, where empathy and trust are mediators. Actual actions of players are recorded and real behaviors explained. In an additional registered experiment, the mediator, empathy, was manipulated to show that it had a positive effect on trust.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.412
Teacher spread0.368 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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