What we know and don't know about great ape cultural communication in the wild
Bibliographic record
Abstract
Following the first descriptions of culture in primates, widespread agreement has developed that the term can be applied to nonhumans as group-specific, socially learned behaviors. While behaviors such as those involving extractive tool use have been researched intensively, we propose that behaviors that are more subtle, less likely to be ecologically constrained, and more likely to be socially shaped, such as cultural forms of communication, provide compelling evidence of culture in nonhuman primates. Additionally, cultural forms of communication can provide novel insights into animal cognition such as the capacity for conformity, conventionalized meanings, arbitrariness in signal forms, and even symbolism. In this paper we focus on evidence from studies conducted on wild great apes. First, we provide a thorough review of what exactly we do know, and by extension don't know, about great ape cultural communication. We argue that detailed research on both vocal and gestural communication in wild great apes shows a more nuanced and variable repertoire than once assumed, with increasing support for group-specific variation. Second, we discuss the relevance of great ape cultural communication and its potential for illustrating evolutionary continuity for human-like cultural attributes, namely cumulative culture and symbolism. In sum, a concerted effort to examine cultural forms of communication in great apes could reveal novel evidence for cultural capacities that have thus far been heavily debated in the literature and can simultaneously contribute to an improved understanding of the complex minds of our closest living relatives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".