Phylogenetic analyses of behavior support existence of culture among wild chimpanzees
Bibliographic record
Abstract
Culture has long been considered to be not only unique to humans, but also responsible for making us qualitatively different from all other forms of life. In recent years, however, researchers studying chimpanzees (Pan troglodytes) have challenged this idea. Natural populations of chimpanzees have been found to vary greatly in their behavior. Because many of these interpopulation differences cannot be readily explained by ecological factors, it has been argued that they result from social learning and, therefore, can be regarded as cultural variations. Recent studies showing social transmission in captive chimpanzee populations suggest that this hypothesis is plausible. However, the culture hypothesis has been questioned on the grounds that the behavioral variation may be explained at a proximate level by genetic differences between subspecies. Here we use cladistic analyses of the major cross-site behavioral data set to test the hypothesis that the behavioral differences among the best-documented chimpanzee populations are genetically determined. If behavioral diversity is primarily the product of genetic differences between subspecies, then population data should show less phylogenetic structure when data from a single subspecies (P. t. schweinfurthii) are compared with data from two subspecies (P. t. verus and P. t. schweinfurthii) analyzed together. Our findings are inconsistent with the hypothesis that the observed behavioral patterns of wild chimpanzee populations can be explained primarily by genetic differences between subspecies. Instead, our results support the suggestion that the behavioral patterns are the product of social learning and, therefore, can be considered cultural.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".