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Teaching is associated with the transmission of opaque culture and leadership across 23 egalitarian hunter-gatherer societies

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  • Zachary H. Garfield

    (University Mohammed VI Polytechnic)

  • Sheina Lew-Levy

    (Durham University)

Abstract

Despite extensive work on the evolution of cooperation, the roles of teaching and leadership in transmitting opaque cultural norms—foundations of cooperative behaviors—are underexplored. Similarly, while teaching is well-studied in the evolution of instrumental culture, little attention is given to its role in transmitting opaque culture, such as social values and norms. Transmitting opaque culture often requires teaching, and group leaders are well-positioned to facilitate this process. Using comparative ethnographic data, we explore teaching, leadership, and instrumental versus opaque culture by examining whether opaque culture is primarily transmitted via teaching, which age groups tend to learn these norms, and whether leaders are disproportionately involved in teaching. Drawing on ethnographic data from 23 egalitarian foraging societies, we find teaching is more strongly associated with transmitting cultural values and kinship knowledge than subsistence skills and is closely linked to opaque culture and leadership. Leader-directed teaching may drive cooperation, suggesting new research avenues.

Suggested Citation

  • Zachary H. Garfield & Sheina Lew-Levy, 2025. "Teaching is associated with the transmission of opaque culture and leadership across 23 egalitarian hunter-gatherer societies," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58764-9
    DOI: 10.1038/s41467-025-58764-9
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    References listed on IDEAS

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    1. Marini, Matteo, 2004. "Cultural evolution and economic growth: a theoretical hypothesis with some empirical evidence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(6), pages 765-784, December.
    2. Axelrod, Robert, 1986. "An Evolutionary Approach to Norms," American Political Science Review, Cambridge University Press, vol. 80(4), pages 1095-1111, December.
    3. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    4. Bailey R. House & Patricia Kanngiesser & H. Clark Barrett & Tanya Broesch & Senay Cebioglu & Alyssa N. Crittenden & Alejandro Erut & Sheina Lew-Levy & Carla Sebastian-Enesco & Andrew Marcus Smith & Sü, 2020. "Universal norm psychology leads to societal diversity in prosocial behaviour and development," Nature Human Behaviour, Nature, vol. 4(1), pages 36-44, January.
    5. Ángel V. Jiménez & Alex Mesoudi, 2019. "Prestige-biased social learning: current evidence and outstanding questions," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-12, December.
    6. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    7. Zachary Garfield & Kristen Syme & Edward H. Hagen, 2020. "Universal and variable leadership dimensions across human societies," Post-Print hal-03162384, HAL.
    8. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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