Rapid cultural adaptation can facilitate the evolution of large-scale cooperation
Why this work is in the frame
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Bibliographic record
Abstract
Over the past several decades, we have argued that cultural evolution can facilitate the evolution of large-scale cooperation because it often leads to more rapid adaptation than genetic evolution, and, when multiple stable equilibria exist, rapid adaptation leads to variation among groups. Recently, Lehmann, Feldman, and colleagues have published several papers questioning this argument. They analyze models showing that cultural evolution can actually reduce the range of conditions under which cooperation can evolve and interpret these models as indicating that we were wrong to conclude that culture facilitated the evolution of human cooperation. In the main, their models assume that rates of cultural adaption are not strong enough compared to migration to maintain persistent variation among groups when payoffs create multiple stable equilibria. We show that Lehmann et al. reach different conclusions because they have made different assumptions. We argue that the assumptions that underlie our models are more consistent with the empirical data on large-scale cultural variation in humans than those of Lehmann et al., and thus, our models provide a more plausible account of the cultural evolution of human cooperation in large groups. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00265-010-1100-3) contains supplementary material, which is available to authorized users.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it