Bibliographic record
Abstract
To answer tantalizing questions such as whether animals are moral or how morality evolved, I propose starting with a somewhat less fraught question: do animals have normative cognition? Recent psychological research suggests that normative thinking, or ought-thought, begins early in human development. Recent philosophical research suggests that folk psychology is grounded in normative thought. Recent primatology research finds evidence of sophisticated cultural and social learning capacities in great apes. Drawing on these three literatures, I argue that the human variety of social cognition and moral cognition encompass the same cognitive capacities and that the nonhuman great apes may also be normative beings. To make this argument, I develop an account of animal social norms that shares key properties with Cristina Bicchieri’s account of social norms but which lowers the cognitive requirements for having a social norm. I propose a set of four early developing prerequisites implicated in social cognition that make up what I call naïve normativity: (1) the ability to identify agents, (2) sensitivity to in-group/out-group differences, (3) the capacity for social learning of group traditions, and (4) responsiveness to appropriateness. I review the ape cognition literature and present preliminary empirical evidence supporting the existence of social norms and nave normativity in great apes. While there is more empirical work to be done, I hope to have offered a framework for studying normativity in other species, and I conclude that we should be open to the possibility that normative cognition is yet another ancient cognitive endowment that is not human-unique. Originally published as: Andrews, K. (2020). Naïve Normativity: The Social Foundation of Moral Cognition. Journal of the American Philosophical Association, 6(1), 36-56. https://doi.org/10.1017/apa.2019.30
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".