Picturing Primates and Looking at Monkeys: Why 21st Century Primatology Needs Wittgenstein
Bibliographic record
Abstract
Abstract The Social Intelligence or Social Brain Hypothesis is an influential theory that aims to explain the evolution of brain size and cognitive complexity among the primates. This has shaped work in both primate behavioural ecology and comparative psychology in deep and far‐reaching ways. Yet, it not only perpetuates many of the conceptual confusions that have plagued psychology since its inception, but amplifies them, generating an overly intellectual view of what it means to be a competent and successful social primate. Here, I present an analysis of the Social Intelligence/Brain hypothesis highlighting how its anthropocentric origins have led us to be held captive by a picture of what social life involves and the kind of mind needed to navigate the social landscape. I go on to consider how experimental work in this vein either does not test what it claims to be testing, or introduces impossible problems regarding animal minds that cannot be solved, but only dissolved. What we need, in other words, is the application of “Wittgenstein's razor” and the reinvention of primatology along his enactivist lines.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.039 |
| Scholarly communication | 0.004 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".