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Record W1528156613 · doi:10.1080/19420889.2015.1017164

The spread of a novel behavior in wild chimpanzees: New insights into the ape cultural mind

2015· article· en· W1528156613 on OpenAlexaff
Thibaud Gruber, Timothée Poisot, Klaus Zuberbühler, William Hoppitt, Catherine Hobaiter

Bibliographic record

VenueCommunicative & Integrative Biology · 2015
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversité du Québec à RimouskiUniversité du Québec à Montréal
FundersBiotechnology and Biological Sciences Research Council
KeywordsTroglodytesSocial learningCaptivityCultural transmission in animalsAnimal behaviorComparative psychologyPsychologyPrimateBehavioural sciencesDevelopmental psychologySocial psychologyBiologyEcologyCognitive psychologyEvolutionary biologyZoologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

For years, the animal culture debate has been dominated by the puzzling absence of direct evidence for social transmission of behavioral innovations in the flagship species of animal culture, the common chimpanzee. Although social learning of novel behaviors has been documented in captivity, critics argue that these findings lack ecological validity and therefore may not be relevant for understanding the evolution of culture. For the wild, it is possible that group-specific behavioral differences emerge because group members respond individually to unspecified environmental differences, rather than learning from each other. In a recent paper, we used social network analyses in wild chimpanzees (Pan troglodytes schweinfurthii) to provide direct evidence for social transmission of a behavioral innovation, moss-sponging, to extract water from a tree hole. Here, we discuss the implications of our findings and how our new methodological approach could help future studies of social learning and culture in wild apes.

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)0.004
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
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 head0.124
GPT teacher head0.413
Teacher spread0.289 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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