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A competitive nonverbal false belief task for children and apes

2009· article· en· W2115276564 on OpenAlexaff
Carla Krachun, Malinda Carpenter, Josep Call, Michael Tomasello

Bibliographic record

VenueDevelopmental Science · 2009
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologyNonverbal communicationTask (project management)Cognitive psychologyFalse beliefTheory of mindDevelopmental psychologyCognition

Abstract

fetched live from OpenAlex

A nonverbal false belief task was administered to children (mean age 5 years) and two great ape species: chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). Because apes typically perform poorly in cooperative contexts, our task was competitive. Two versions were run: in both, a human competitor witnessed an experimenter hide a reward in one of two containers. When the competitor then left the room (version A) or turned around (version B), the experimenter switched the locations of the containers. The competitor returned and reached with effort, but unsuccessfully, towards the incorrect container. Children displayed an understanding of the competitor's false belief by correctly choosing the other container to find the reward. Apes did not. However, in version A (but not version B), apes looked more often at the unchosen container in false belief trials than in true belief control trials, possibly indicating some implicit or uncertain understanding that needs to be investigated further.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.270
Teacher spread0.262 · 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

Citations182
Published2009
Admission routes1
Has abstractyes

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