Embodied cognitive evolution and the limits of convergence
Bibliographic record
Abstract
Comparative psychology seems to be perpetually bogged down in intractable debates about which species have what cognitive capacities, which criteria to use and whether or not the capacities are domain general. The problem arises from lack of conceptual clarity about how to define, measure and compare cognitive capacities. In turn, conceptual vagueness arises from the use of anthropocentric folk-psychological concepts given apparent scientific legitimacy by framing them in cognitivist, computational terms. This 'cognitivist gambit' assumes that cognitive processes necessarily involve representations that are independent of the sensory-motor specializations associated with different body plans and ecological niches. We argue instead that sensory-motor adaptations are not inconvenient confounding variables that should be controlled to isolate cognition, but intrinsic aspects of cognitive evolution. This perspective implies that, because bodies and their sensory-motor control are highly divergent across the tree of life, comparative psychology should pay more attention to phylogenetic constraint and divergent cognitive evolution. It also implies that boiling down neuro-cognitive evolution to brain size or numbers of neurons will fail to capture the richness and complexity of the interrelationships between nervous systems, cognition, behaviour and ecology. If correct, this perspective suggests a need to reconsider the ontological basis of comparative psychology.This article is part of the Theo Murphy meeting issue 'Selection shapes diverse animal minds'.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".