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Record W2062941155 · doi:10.1371/journal.pone.0061804

Children’s Use of Communicative Intent in the Selection of Cooperative Partners

2013· article· en· W2062941155 on OpenAlexafffund
Kristen A. Dunfield, Valerie A. Kuhlmeier, Lindsay Murphy

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsQueen's UniversityConcordia University
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsVariety (cybernetics)Selection (genetic algorithm)Free rider problemPsychologySocial psychologyCognitive psychologyComputer scienceMicroeconomicsArtificial intelligenceEconomics

Abstract

fetched live from OpenAlex

Within the animal kingdom, human cooperation represents an outlier. As such, there has been great interest across a number of fields in identifying the factors that support the complex and flexible variety of cooperation that is uniquely human. The ability to identify and preferentially interact with better social partners (partner choice) is proposed to be a major factor in maintaining costly cooperation between individuals. Here we show that the ability to engage in flexible and effective partner choice behavior can be traced back to early childhood. Specifically, across two studies, we demonstrate that by 3 years of age, children identify effective communication as "helpful" (Experiments 1 & 2), reward good communicators with information (Experiment 1), and selectively reciprocate communication with diverse cooperative acts (Experiment 2). Taken together, these results suggest that even in early childhood, humans take advantage of cooperative benefits, while mitigating free-rider risks, through appropriate partner choice behavior.

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 score0.546
Threshold uncertainty score0.485

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 head0.099
GPT teacher head0.301
Teacher spread0.202 · 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

Citations39
Published2013
Admission routes2
Has abstractyes

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