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Record W2167673844 · doi:10.46867/c4vp4p

Naturalistic Approaches to Orangutan Intelligence and the Question of Enculturation

2012· article· en· W2167673844 on OpenAlexafffund
Anne E. Russon

Bibliographic record

VenueInternational Journal of Comparative Psychology · 2012
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsYork University
FundersYork University
KeywordsEnculturationArboreal locomotionPsychologyCognitionNaturalismCognitive psychologyCognitive scienceEpistemologyEcologyNeuroscience

Abstract

fetched live from OpenAlex

Field studies have been, and continue to be, important contributors to the understanding of great ape cognition-especially with regard to questions of cognitiveecology or the key cognitive challenges in the evolution of primate intelligence. Theyare also critical to resolving a current debate, whether human enculturation boosts great apes' cognition, because only studies of problem-solving in feral contexts can resolve the question of whether abilities are higher in enculturated than non-enculturated great apes. To this debate, this paper offers findings from observational field studies on freeranging rehabilitant orangutans' cognitive capabilities, as revealed in their food processing and arboreal positioning, and on the possible social transmission of that expertise. These findings are combined with published findings on wild and enculturated great apes as a basis for assessing the effects of human enculturation on great ape cognition. This assessment joins several others in showing that free-ranging great apes independently achieve cognition of the same order of complexity as enculturated great apes, in concluding that claims for the effects of human enculturation are likely inflated, and in suggesting that the basis for the effectiveness of human enculturation is that great apes normally "enculturate" themselves.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.271
GPT teacher head0.474
Teacher spread0.203 · 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

Citations10
Published2012
Admission routes2
Has abstractyes

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