Bibliographic record
Abstract
Introduction Since the classic studies on potato and wheat washing in Japanese macaques (Kawai, 1965), traditions have often been studied in nonhuman animals because they represent an important precursor to human culture. This anthropocentric program has led many researchers to study primates and to focus on cognitive traits that are associated with human culture, for example imitation, language, tool use, and theory of mind. In this perspective, the study of nonhuman culture has recently culminated in the demonstration that wild chimpanzees in seven African populations show as many as 39 behavioral variants that may be attributed to “culture” (Whiten et al ., 1999). For psychologists and anthropologists, the concern with precursors of human behavior in the closest relatives of Homo sapiens is perfectly justified. For biologists, however, the evolution of cognition must be studied on a much broader and phylogenetically distant set of taxa; in comparative biology (Harvey and Pagel, 1991), one of the goals is to remove phylogenetic influences from taxonomic data and to look for independent evolution of traits as adaptations to particular ecological and life-history conditions. In this chapter, we compare the origin and diffusion of new feeding behaviors in birds and mammals. We begin by explaining why birds are particularly suitable to a comparison with mammals, and we discuss the use of anecdotal reports in the study of cognition. We then highlight three features by which the current literature on birds appears to differ from that on mammals and propose hypotheses to explain the differences.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".