Tribal Social Instincts and the Cultural Evolution of Institutions to Solve Collective Action Problems
Bibliographic record
Abstract
Human social life is uniquely complex and diverse. Much of that complexity and diversity arises from culturally transmitted ideas, values and skills that underpin the operation of social norms and institutions that structure our social life. Considerable theoretical and empirical work has been devoted to the role of cultural evolutionary processes in the evolution of social norms and institutions. The most persistent controversy has been over the role of cultural group selection and gene-culture coevolution in early human populations during Pleistocene. We argue that cultural group selection and related cultural evolutionary processes had an important role in shaping the innate components of our social psychology. By the Upper Paleolithic humans seem to have lived in societies structured by institutions, as do modern populations living in small-scale societies. The most ambitious attempts to test these ideas have been the use of experimental games in field settings to document human similarities and differences on theoretically interesting dimensions. These studies have documented a huge range of behavior across populations, although no societies so far examined follow the expectations of selfish rationality. These data are at least consistent with operation of cultural group selection and gene-culture coevolution operating in the deep tribal past and with the contemporary importance of cultural evolution in the evolution of institutions and institutional diversity.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".