Naturalism in the social sciences : a short review

“Naturalizing” social sciences ?

Naturalism is a family of philosophical and scientific positions broadly stating that all observable phenomenon are part to the same causally integrated world. Natural scientist typically work toward explain those phenomenons by exposing and formalizing underlying causal relations, notably through building mechanical models and testing their predictions in experimental settings (Craver and Tabery 2019). While this perspective has been highly successful in identifying universal laws in the physical science, it is at the moment marginal in the social sciences and generally understood to be unadapted to the complexity of human beings.

Yet, the life sciences exemplify how a naturalist approach can apply to such complex systems, differing significantly in their practice and structure to what we understand as “hard”, formal science. Physical scientists routinely study systems which respond to stimulation in a regular and predictible way, allowing them to state mathematically tractable laws which are a sufficient description of said system in a given context. A life scientist, on the other hand, is rarely in any position to mentally isolate two dynamics of the systems they study. On the contrary, living organism are organized at multiple imbricated scales, and explicative models must integrate these in the explanation of any phenomenon (Mitchell 2003).

The question of whether the natural sciences can indeed address the complexity of societies, or even of what it would mean, is therefore an open one. The purpose of the present article is to help answer it by presenting the main research programs associated to naturalism in the social sciences, their approach and their central results. This article is primarily intended as a map of naturalist social sciences one can access at any time or explore at their own pace, but it may also provide anyone who wants to build an ensemble vision of these disciplines with the means to do so. In any case, it lacks any central thesis, or any intended take-home message one is expected to receive by reading this article.

The disciplines reviewed here embody widely different approaches, and very different understanding of naturalism as a scientific philosophy. Evolutionary psychology bases its understanding of human behavior on the functional constraints of their past ecology, and typically aims to rebuild social sciences from the ground up based on their understanding of human psychology. Cliodynamics, on the other hand, grounds its approach directly in preexisting paradigms of history or social sciences, while introducing natural scientific standards for the formalization and test of theories. Cultural evolution, finally, studies human culture and societies as an evolutionary system, without any preferred scale of analysis or specific methodological standards. All of these approaches are explicit attempts at naturalizing the social sciences, all of them massively import concepts and methods from the life sciences, all of them are massively overstated in their scope by both opponents and sympathizers. While I cannot articulate an extensive review of these disciplines, much less in one single article, I hope to give the reader a perspective of their fundamental approaches, their relation to each other, and their central findings.

Analyzing human psychology

Evolutionary psychology is typically understood as the study of human behavior as a collection of evolutionary traits, which exist due to their ability to enable an individual’s survival and reproduction. Such reasoning is endemic in the evolutionary science, where it is common that an organism has specific properties that are both genetically heritable (they are to some extent caused by the organism’s genetic information, and are therefore passed to descendants) and adaptive (they cause this organism to spread their genetic information further, by having more descendants). Such traits are said to fulfill some evolutionary “function” to the organism : as an example, humans have kidneys because kidneys efficiently filtrate toxins, and human ancestors which were comparatively less able to filtrate toxins had comparatively higher death rate.

As human psychology is driven by a cognitive structure that is in part genetically heritable, this line of argumentation is in principle valid in its context. Evolutionary psychology is however radical in its attribution of functionality to a wide array of human behavioral regularities, in contrast to the supposedly conservative way evolutionary biology defines and studies evolutionary traits (Bateson and Laland 2013, 201) The underlying argument is that human psychology follow a property of “massive modularity” allowing the scientist to methodologically reduce it to isolated mechanisms oriented toward specific functions (Barrett and Kurzban 2006). Indeed, any instance of stereotypical behavior with strong adaptive consequences is likely to have emerged due to selection of semi-autonomous mechanisms (the so-called “modules”) underlying it at some point in the past, and to have remained adaptive until now (or until a recent period). Importantly, such modules are deep structures which are typically not accessible to introspection, which provides a prior to look for causes of contemporary behavioral patterns in their ecological meaning to our common ancestors rather, than in the reasons humans invoke to explain their choices.

While humans are to some extent more individually intelligent than other primates, their most exceptional features are related to the way they interact and communicate with each other, allowing them to organize as functional social groups (Wilson, Van Vugt, and O’Gorman 2008) and to navigate the politics of such groups (Leech and Cronk 2017). Most basically, their brain development allows humans to handle a large number of social relation (R. I. M. Dunbar and Shultz 2007) and to organize collective action (Gavrilets 2015), which combined to their preference for fairness in social relations complicates aggression as a strategy (Wrangham 2019; Shilton et al. 2020). These basic adaptations to collective life in turn allow human societies to develop an array of collaborative structures (Boehm 2009; Wilson, Ostrom, and Cox 2013), therefore extending the domain of cooperation and most importantly facilitating the development of complex skills through social learning through extending a long juvenile period (Burkart, Hrdy, and Schaik 2009; P. J. Richerson and Boyd 2020). This array of psychological traits, along with the social, ecological and cultural features they enable, work as a “human evolutionary complex” in the sense each of them does not predict much of human ecology in isolation, but their interplay constitute a dynamic fundamental to the evolution of modern humans.

A common thread to these psychological adaptations, both in their ancestral and contemporary expressions, is their ambivalence between egoist and prosocial functions. As a paradigmatic example, seemingly altruistic behavior such as grooming and other forms of interpersonal care appear to be in part driven by individual adaptation to maintain economic and political relations (Barclay 2013), while still being essential to social cohesion (R. Dunbar 1998). The same argument holds for internalization of social norms (morality) (Gavrilets and Richerson 2017) and for social identity (Harvey Whitehouse and Lanman 2014), which benefits to the individual are mediated by reputation rather than interpersonal cooperation (Barclay 2013). The case of language is however the most interesting : a central adaptation to social cohesion (R. Dunbar 1998), coordination (E. A. Smith 2010), and reinforcement of social norms (D. Smith et al. 2017) ; language also serves to further an individual’s political interest through coalition management (Dessalles 2014) and motivated reasoning (Mercier 2011). In other words, while language as a social phenomenon is the backbone of human social organization, its recruitment in reasoning is driven to further one’s influence upon others rather than build reflexivity upon one’s action.

Evolutionary psychology is therefore relevant to address the large array of social behavior underlying the cohesion of human societies, even though its somewhat loose use of adaptive claims earns it a reputation of pseudoscientificity (S. E. Smith 2020). In particular, it is extremely apt to capture and formalize the interplay between imbricated levels of social organization by exposing how their cognition allows humans both to maintain a cohesive social structure and to exploit it to their personal advantage - and often through the very same psychological mechanisms. Evolutionary psychology as a social science fails however to consider emerging effects from complex patterns of interaction (Guénin–Carlut 2020), which is made even more stringent by the insistence from prominent sympathizers that their discipline is a sufficient alternative to preestablished social sciences.

History as a (predictive) science

Cliodynamics is defined by its main proponent as “history as science”, referring through this expression to any attempt at drawing a natural history of human societies by exposing some of the causal or dynamical structures driving them (Turchin 2008; 2011). This discipline integrates therefore any attempt at articulating laws of human history, either through modeling, data science or historical analysis, and does not exist in relation to a specific theoretical or methodological core. Such laws are to be understood as formal descriptions of empirical patterns rather than statement of a priori truth, which in principle may exist at any scale of analysis from the most microscopic (how power brokers negotiate influence) to the most macroscopic (how societies develop in the long run). Unlike evolutionary psychology, cliodynamics is in its theories and concepts a direct heir to the social sciences, and it is in fact dubious that many de facto cliodynamists see themselves as such rather than as computationally inclined participants to archaeology, economy, or geography.

Cliodynamics is therefore a rather decentralized project. Yet, its most influential and radical embodiment is unarguably the SESHAT data bank project (Turchin et al. 2018; H. Whitehouse et al. 2016), which aim is to aggregate anthropologically relevant knowledge about every cultural area since the Neolithic in a computationally tractable manner. SESHAT proponents hope to integrate work across disciplines into a meaningful framework for deep history, or longue durée history, or in other works the study of structural drives of change in human societies. This framework is most notable in allowing to diagnose functionality in social forms : for example, low intensity, high frequency rituals enable better social coordination while high intensity, low frequency rituals facilitate extreme cooperation (Atkinson and Whitehouse 2011), and both seem to emerge preferentially when relevant in organizing local brands of collective action problems (Botero et al. 2014). The focus of SESHAT research is however to study the progressive scaling up of human organization since the Neolithic, both by exposing its drivers and its social mechanisms. It appears at the moment that highly hierarchical State societies emerge as an adaptation to intense inter-group conflict (Turchin 2010), and that moralistic religiosity allowed their posterior growth by facilitating social and economic coordination within such policies (Turchin et al. 2019).

While SESHAT equipped itself with best practice tools to study structural causes in human history, it is neither the first nor the most visible attempt at describing long term geographical or institutional determinism in the development of societies. Institutional economics are for example familiar with studying long past institutions or other cultural traits as leading causes in the development of societies (Spolaore and Wacziarg 2013). In turn, they can study the socio-political context that allowed their emergence : as an example, the political power amassed by the bourgeoisie class through the Atlantic slave trade was proposed as a key cause to the institutional revolution defining modern capitalism (Acemoglu, Johnson, and Robinson 2002). The most ambitious attempts at theorizing long run determinism in human societies focus not on the effects of institutions, however, but on what ecological factors drive the development of those institutions. For example, cereal productivity and a geography favorable to long distance exchanges were proposed to be fundamental to the emergence of hierarchical State societies (Scott 2017). Such factors also appear to constrain the emergence of highly efficient technologies, government, and economic institutions, most notably allowing West European policies to build a differential advantage eventually enabling their aggressive colonization of most of the planet (Diamond 1997).

Cliodynamics also integrate the study of finer grained dynamics, notably regarding the dynamics of power in State societies. A founding result of cliodynamics, the structural-demographic theory, postulates that centralized societies undergo secular cycles of integration and disintegration because of the dynamics of elite struggle for power (Goldstone 2017; Turchin 2007). Indeed, institutional stability depends on a widespread willingness to cooperate within the context of institutions, which itself is contingent on the existence of a feeling of collective identity, historically named “asabiyyah” by the medieval scholar Ibn Khaldun and conserved in socio-cognitive anthropology (Atkinson and Whitehouse 2011). When a State undergo a long period of stability, the asabiyyah of its ruling elite tends to degrade due to internal conflict for power capture, causing them to overburden commoners and to eventually undermine the institutions granting their power. In the medieval north african context described by Khaldun, this usually led to an invasion by Berber nomads and a change in the ruling dynasty. While this last point does not necessarily holds in an intercultural comparison, the general coordinated cyclicity of institutional strength and well-being remains valid in State society (Turchin and Nefedov 2009), mirroring negatively a documented ability for horizontal governance to remain stable through time (Wilson, Ostrom, and Cox 2013; Ostrom 2009).

Cliodynamics cannot be considered an autonomous discipline within social sciences, as it lacks any theoretical or methodological coherence, and is conceptually driven by mainstream social scientific work. Its particularity resides only in its commitment to the epistemology of “laws” and “prediction”, translating a belief that competing hypotheses about the causes of social and cultural change can be formally expressed and tested empirical, for example through a posteriori natural experiments. Even though they also draw from cognitive anthropology and evolutionary science, most cliodynamists work with concepts associated to institutional social sciences, which fits closely with their intention to describe dynamics of social change in the most pragmatic and parsimonious way possible.

Evolving culture

Cultural evolution is at its core the study of how socially transmitted information shaping behavior changes over time. This characterization, while it does not imply a rigid analogy to genetic evolution, is evolutionary in nature (Mesoudi 2016b; 2016a) and implies the possibility to recruit tools built within biological evolutionary theory to study social phenomenons (Mesoudi, Whiten, and Laland 2006). Its defining intention is neither a thematic one, like evolutionary psychology, nor methodological, like cliodynamics. It is therefore ontological, in the sense that any work that consider the processes of social inheritance as constitutive of culture or to human ecology is cultural evolutionary in essence. This definition is inclusive in the wide array of divergent approaches it encompasses, but strict in its commitment to evolution theory as a formal, predictive framework. For example, it unambiguously excludes the so-called XIXth century theory of “evolutionary anthropology” which viewed human history as a natural progress toward civilized (west European) societies - a form of teleological reasoning that has no grounding in evolution theory whatsoever.

Early work focused on how the psychology of social learning could cause adaptive behavior to spread preferentially in a way that makes constitutive of evolutionary selection (Boyd and Richerson 1988; Cavalli-Sforza and Feldman 1981). Human are indeed adapted to understand other individual’s intentions, making them particularly apt to reproduce complex objective-oriented behavior (Tomasello and Carpenter 2007; Tomasello and Moll 2010). In addition, they are biased to reproduce cultural traits that seem especially relevant due to their content (eg : food norms, social markers, intuitive ideas) or due to who display them (especially skillful or otherwise successful individuals). This high proficiency and selectivity in social learning causes useful cultural traits to spread preferentially, and in the case of technology or language causes increasingly efficient traits to emerge (Boyd, Richerson, and Henrich 2013; Kirby, Cornish, and Smith 2008). In turn, cultural evolved traits may cause posterior genetic evolution, as in the case of lactose tolerance which evolved in Europe because of the generalization of cattle farming (Beja-Pereira et al. 2003). The view drafted above of culture and genes as two dynamically interacting domains of human evolution has defined the “Dual Inheritance Theory” and founded the study of culture in an evolutionary framework (P. J. Richerson and Boyd 2008).

Unsurprisingly, major debates in contemporary research are defined by diverging interpretations of this early characterization. While a majority of cultural evolution researchers follows quite literally the idea of gene-culture coevolution, some criticize the notion of culture as evolutionary because of the dissimilarity between idealized models of evolutionary inheritance without information loss and the actual mechanisms of cultural transmission (Acerbi and Mesoudi 2015). These researchers argue that culture undergo “attraction” toward content that is maximally easy to conceive and transmit rather than “evolution” stricto sensu (Sperber and Hirschfeld 2004; Sperber 1994), and that a detailed understanding of human cognition is of more value to cultural evolution than adaptive reasoning. While successful in the evolution of language and more generally cultural content (Morin 2018; Acerbi and Alexander Bentley 2014), radical extensions of Dual Inheritance Theory show more relevance in social evolution due to their ability to address irreducibly collective behavior. Central examples are the study of culturally mediated alterations of human environment as a mode of evolutionary inheritance (Laland, Odling‐Smee, and Feldman 2001), and the consideration of group-level selection of cultural traits (P. Richerson et al. 2016). These approaches extend cultural evolutionary theory from the study of individual representations to the study of social systems, such as institutions (Smaldino 2014) or socio-economic morphology (Rowley-Conwy and Layton 2011).

Developed cultural evolutionary fields typically integrate cognitive (how individuals learn and relate to practices) and functional (how practices work so as to regulate societies) interpretation of practices in their study of how and why they emerge. Social norms, a key element of cultural evolutionary theory, are for example studied (in addition to their innate psychology, which we discussed earlier) from the perspective of their function, transmission, and reinforcement. Storytelling behavior, while adaptive at an individual level due to increased status of storytellers, is driven toward content diffusing socially beneficial norms, with measurable effects on groups ability to coordinate (D. Smith et al. 2017). Rituals modality reinforce contextually adaptive behavior, with highly dysphoric low frequency rituals facilitating extreme cooperation and emotionally neutral high frequency rituals facilitating large scale cooperation (Atkinson and Whitehouse 2011) through actively studied cognitive mechanisms (Harvey Whitehouse and Lanman 2014). The field of greatest integration of cognitive and adaptive explanations to social behavior is perhaps the study of religion, with mainstream research displaying both how belief in supernatural entities emerges from human cognitive invariants (Atran and Norenzayan 2004; Atran and Henrich 2010), how omniscient, omnipotent, and morally motivated “Big Gods” catalyze widespread cooperation (Norenzayan et al. 2016), and how religions promoting such gods drove socio-political integration (Turchin et al. 2019).

While debate over whether social learning constitutes true evolutionary inheritance obscures its scope and definition, cultural evolution provides a framework for studying the patterns of change and stability of human societies and cultures. It includes a wide array of transdisciplinary works recruiting evolutionary tools in social sciences, such as the study of phylogeny and the coevolution of institutions (Mace and Jordan 2011; Basava, Zhang, and Mace 2021) and other approaches amounting to cliodynamics (Turchin et al. 2019; 2020). It is especially relevant in its study of the interaction between the social function of cultural traits and their psychological foundations, which it addresses through classical evolutionary study of function, mechanisms, and inheritance (Bateson and Laland 2013). Its main importance is however its explicit integration of culture as an important level of human evolution, core to the adaptive dynamics constitutive of our species (Muthukrishna and Henrich 2016).

Conclusion

I drafted above a concise review of three research programs central to naturalism in the social sciences, presenting their fundamental approaches and their main results. The goal of this article is twofold. First, it documents in a synthetic manner the scientific basis of the work we aim to develop at Kairos Cliodynamics. Second, it provides precise elements regarding their scope and assumptions, which may enable informed debate on their relevance within a broader scientific context. I hope to have articulated a clear, if not especially accessible, synthesis of the naturalist social sciences that will catalyze further scientific or epistemological reflection on the matter.

Due to its density and lack of a central thesis, I suggest the present article should be treated as a rough cognitive map to contemporary research, and be navigated as such. Readers may choose to come back to it to contextualize what they will be reading in the future, or to deepen their understanding of a specific theoretical or empirical point by reading referenced articles. In any way, this article is not intended to provide much insight in and of itself, but rather to enable an active effort of cross-referencing or autonomous reflection on the reader’s part by helping them frame their future encounters with cultural evolution and naturalism in the social sciences.

Bibilography

  • Acemoglu, Daron, Simon Johnson, and James Robinson. 2002. “The Rise of Europe: Atlantic Trade, Institutional Change and Economic Growth.” Working Paper 9378. Working Paper Series. National Bureau of Economic Research. https://doi.org/10.3386/w9378.
  • Acerbi, Alberto, and R. Alexander Bentley. 2014. “Biases in Cultural Transmission Shape the Turnover of Popular Traits.” Evolution and Human Behavior 35 (3): 228–36. https://doi.org/10.1016/j.evolhumbehav.2014.02.003.
  • Acerbi, Alberto, and Alex Mesoudi. 2015. “If We Are All Cultural Darwinians What’s the Fuss about? Clarifying Recent Disagreements in the Field of Cultural Evolution.” Biology & Philosophy 30 (4): 481–503. https://doi.org/10.1007/s10539-015-9490-2.
  • Atkinson, Quentin D., and Harvey Whitehouse. 2011. “The Cultural Morphospace of Ritual Form: Examining Modes of Religiosity Cross-Culturally.” Evolution and Human Behavior 32 (1): 50–62. https://doi.org/10.1016/j.evolhumbehav.2010.09.002.
  • Atran, Scott, and Joseph Henrich. 2010. “The Evolution of Religion: How Cognitive By-Products, Adaptive Learning Heuristics, Ritual Displays, and Group Competition Generate Deep Commitments to Prosocial Religions.” Biological Theory 5 (1): 18–30. https://doi.org/10.1162/BIOT_a_00018.
  • Atran, Scott, and Ara Norenzayan. 2004. “Religion’s Evolutionary Landscape: Counterintuition, Commitment, Compassion, Communion.” Behavioral and Brain Sciences 27 (6): 713–30. https://doi.org/10.1017/S0140525X04000172.
  • Barclay, Pat. 2013. “Strategies for Cooperation in Biological Markets, Especially for Humans,” 2013.
  • Barrett, H. Clark, and Robert Kurzban. 2006. “Modularity in Cognition: Framing the Debate.” Psychological Review 113 (3): 628–47. https://doi.org/10.1037/0033-295X.113.3.628.
  • Basava, Kiran, Hanzhi Zhang, and Ruth Mace. 2021. “A Phylogenetic Analysis of Revolution and Afterlife Beliefs.” Nature Human Behaviour, January, 1–8. https://doi.org/10.1038/s41562-020-01013-4.
  • Bateson, Patrick, and Kevin N. Laland. 2013. “Tinbergen’s Four Questions: An Appreciation and an Update.” Trends in Ecology & Evolution 28 (12): 712–18. https://doi.org/10.1016/j.tree.2013.09.013.
  • Beja-Pereira, Albano, Gordon Luikart, Phillip R. England, Daniel G. Bradley, Oliver C. Jann, Giorgio Bertorelle, Andrew T. Chamberlain, et al. 2003. “Gene-Culture Coevolution between Cattle Milk Protein Genes and Human Lactase Genes.” Nature Genetics 35 (4): 311–13. https://doi.org/10.1038/ng1263.
  • Boehm, Christopher. 2009. Hierarchy in the Forest: The Evolution of Egalitarian Behavior. Harvard University Press.
  • Botero, Carlos A., Beth Gardner, Kathryn R. Kirby, Joseph Bulbulia, Michael C. Gavin, and Russell D. Gray. 2014. “The Ecology of Religious Beliefs.” Proceedings of the National Academy of Sciences 111 (47): 16784–89. https://doi.org/10.1073/pnas.1408701111.
  • Boyd, Robert, and Peter J. Richerson. 1988. Culture and the Evolutionary Process. University of Chicago Press.
  • Boyd, Robert, Peter J. Richerson, and Joseph Henrich. 2013. “The Cultural Evolution of Technology: Facts and Theories,” 2013.
  • Burkart, J. M., S. B. Hrdy, and C. P. Van Schaik. 2009. “Cooperative Breeding and Human Cognitive Evolution.” Evolutionary Anthropology: Issues, News, and Reviews 18 (5): 175–86. https://doi.org/10.1002/evan.20222.
  • Cavalli-Sforza, Luigi Luca, and Marcus W. Feldman. 1981. Cultural Transmission and Evolution: A Quantitative Approach. Princeton University Press.
  • Craver, Carl, and James Tabery. 2019. “Mechanisms in Science.” In The Stanford Encyclopedia of Philosophy, edited by Edward N. Zalta, Summer 2019. Metaphysics Research Lab, Stanford University. https://plato.stanford.edu/archives/sum2019/entries/science-mechanisms/.
  • Dessalles, Jean-Louis. 2014. “Why Talk ?” In The Social Origins of Language.
  • Diamond, Jared M. 1997. Guns, Germs, and Steel: The Fates of Human Societies. W.W. Norton.
  • Dunbar, R. I. M., and Susanne Shultz. 2007. “Evolution in the Social Brain.” Science 317 (5843): 1344–47. https://doi.org/10.1126/science.1145463.
  • Dunbar, Robin. 1998. Grooming, Gossip, and the Evolution of Language. Harvard University Press.
  • Gavrilets, Sergey. 2015. “Collective Action and the Collaborative Brain.” Journal of The Royal Society Interface 12 (102): 20141067. https://doi.org/10.1098/rsif.2014.1067.
  • Gavrilets, Sergey, and Peter J. Richerson. 2017. “Collective Action and the Evolution of Social Norm Internalization,” 2017.
  • Goldstone, Jack A. 2017. “Demographic Structural Theory: 25 Years On,” 29.
  • Guénin–Carlut, Avel. 2020. “Cognition in Eco, Cognition in Vitro - Measurement and Explanation in Cognitive Science,” March. https://doi.org/10.17605/OSF.IO/ERCZ6.
  • Kirby, Simon, Hannah Cornish, and Kenny Smith. 2008. “Cumulative Cultural Evolution in the Laboratory: An Experimental Approach to the Origins of Structure in Human Language.” Proceedings of the National Academy of Sciences 105 (31): 10681–86. https://doi.org/10.1073/pnas.0707835105.
  • Laland, K. N., J. Odling‐Smee, and M. W. Feldman. 2001. “Cultural Niche Construction and Human Evolution.” Journal of Evolutionary Biology 14 (1): 22–33. https://doi.org/10.1046/j.1420-9101.2001.00262.x.
  • Leech, Beth L., and Lee Cronk. 2017. “Coordinated Policy Action and Flexible Coalitional Psychology: How Evolution Made Humans so Good at Politics.” Cognitive Systems Research 43 (June): 89–99. https://doi.org/10.1016/j.cogsys.2017.01.001.
  • Mace, Ruth, and Fiona M. Jordan. 2011. “Macro-Evolutionary Studies of Cultural Diversity: A Review of Empirical Studies of Cultural Transmission and Cultural Adaptation.” Philosophical Transactions of the Royal Society B: Biological Sciences 366 (1563): 402–11. https://doi.org/10.1098/rstb.2010.0238.
  • Mercier, Hugo. 2011. “On the Universality of Argumentative Reasoning.” Journal of Cognition and Culture 11 (1–2): 85–113. https://doi.org/10.1163/156853711X568707.
  • Mesoudi, Alex. 2016a. “Cultural Evolution: Integrating Psychology, Evolution and Culture.” Current Opinion in Psychology, Evolutionary psychology, 7 (February): 17–22. https://doi.org/10.1016/j.copsyc.2015.07.001.
  • ———. 2016b. “Cultural Evolution: A Review of Theory, Findings and Controversies.” Evolutionary Biology 43 (4): 481–97. https://doi.org/10.1007/s11692-015-9320-0.
  • Mesoudi, Alex, Andrew Whiten, and Kevin N. Laland. 2006. “Towards a Unified Science of Cultural Evolution.” Behavioral and Brain Sciences 29 (4): 329–47. https://doi.org/10.1017/S0140525X06009083.
  • Mitchell, Sandra D. 2003. Biological Complexity and Integrative Pluralism. Cambridge University Press.
  • Morin, Olivier. 2018. “Spontaneous Emergence of Legibility in Writing Systems: The Case of Orientation Anisotropy.” Cognitive Science 42 (2): 664–77. https://doi.org/10.1111/cogs.12550.
  • Muthukrishna, Michael, and Joseph Henrich. 2016. “Innovation in the Collective Brain.” Philosophical Transactions of the Royal Society B: Biological Sciences 371 (1690): 20150192. https://doi.org/10.1098/rstb.2015.0192.
  • Norenzayan, Ara, Azim F. Shariff, Will M. Gervais, Aiyana K. Willard, Rita A. McNamara, Edward Slingerland, and Joseph Henrich. 2016. “The Cultural Evolution of Prosocial Religions.” Behavioral and Brain Sciences 39. https://doi.org/10.1017/S0140525X14001356.
  • Ostrom, Elinor. 2009. “A General Framework for Analyzing Sustainability of Social-Ecological Systems.” Science 325 (5939): 419–22. https://doi.org/10.1126/science.1172133.
  • Richerson, Peter, Ryan Baldini, Adrian V. Bell, Kathryn Demps, Karl Frost, Vicken Hillis, Sarah Mathew, et al. 2016. “Cultural Group Selection Plays an Essential Role in Explaining Human Cooperation: A Sketch of the Evidence.” Behavioral and Brain Sciences 39. https://doi.org/10.1017/S0140525X1400106X.
  • Richerson, Peter J., and Robert Boyd. 2008. Not By Genes Alone: How Culture Transformed Human Evolution. University of Chicago Press.
  • ———. 2020. “The Human Life History Is Adapted to Exploit the Adaptive Advantages of Culture.” Philosophical Transactions of the Royal Society B: Biological Sciences 375 (1803): 20190498. https://doi.org/10.1098/rstb.2019.0498.
  • Rowley-Conwy, Peter, and Robert Layton. 2011. “Foraging and Farming as Niche Construction: Stable and Unstable Adaptations.” Philosophical Transactions of the Royal Society B: Biological Sciences 366 (1566): 849–62. https://doi.org/10.1098/rstb.2010.0307.
  • Scott, James C. 2017. Against the Grain: A Deep History of the Earliest States. Yale University Press.
  • Shilton, Dor, Mati Breski, Daniel Dor, and Eva Jablonka. 2020. “Human Social Evolution: Self-Domestication or Self-Control?” Frontiers in Psychology 11. https://doi.org/10.3389/fpsyg.2020.00134.
  • Smaldino, Paul E. 2014. “The Cultural Evolution of Emergent Group-Level Traits.” Behavioral and Brain Sciences 37 (3): 243–54. https://doi.org/10.1017/S0140525X13001544.
  • Smith, Daniel, Philip Schlaepfer, Katie Major, Mark Dyble, Abigail E. Page, James Thompson, Nikhil Chaudhary, et al. 2017. “Cooperation and the Evolution of Hunter-Gatherer Storytelling.” Nature Communications 8 (1): 1–9. https://doi.org/10.1038/s41467-017-02036-8.
  • Smith, Eric Alden. 2010. “Communication and Collective Action: Language and the Evolution of Human Cooperation.” Evolution and Human Behavior 31 (4): 231–45. https://doi.org/10.1016/j.evolhumbehav.2010.03.001.
  • Smith, Subrena E. 2020. “Is Evolutionary Psychology Possible?” Biological Theory 15 (1): 39–49. https://doi.org/10.1007/s13752-019-00336-4.
  • Sperber, Dan. 1994. “The Epidemiology of Representations.” Mapping the Mind: Domain Specificity in Cognition and Culture, 39.
  • Sperber, Dan, and Lawrence A. Hirschfeld. 2004. “The Cognitive Foundations of Cultural Stability and Diversity,” 2004.
  • Spolaore, Enrico, and Romain Wacziarg. 2013. “How Deep Are the Roots of Economic Development?” Journal of Economic Literature 51 (2): 325–69. https://doi.org/10.1257/jel.51.2.325.
  • Tomasello, Michael, and Malinda Carpenter. 2007. “Shared Intentionality.” Developmental Science 10 (1): 121–25. https://doi.org/10.1111/j.1467-7687.2007.00573.x.
  • Tomasello, Michael, and Henrike Moll. 2010. “The Gap Is Social: Human Shared Intentionality and Culture.” In Mind the Gap: Tracing the Origins of Human Universals, edited by Peter M. Kappeler and Joan Silk, 331–49. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-02725-3_16.
  • Turchin, Peter. 2007. War and Peace and War : The Rise and Fall of Empires.
  • ———. 2008. “Arise ‘Cliodynamics.’” Nature 454 (7200): 34–35. https://doi.org/10.1038/454034a.
  • ———. 2010. “Warfare and the Evolution of Social Complexity: A Multilevel-Selection Approach.” Structure and Dynamics 4 (3). https://escholarship.org/uc/item/7j11945r.
  • ———. 2011. “Toward Cliodynamics – an Analytical, Predictive Science of History” 2: 21.
  • Turchin, Peter, Daniel Hoyer, Andrey Korotayev, Nikolay Kradin, Sergei Nefedov, Gary Feinman, James S. Bennett, Pieter Francois, and Harvey Whitehouse. 2020. “Rise of the War Machines: Charting the Evolution of Military Technologies from the Neolithic to the Industrial Revolution.” SocArXiv. https://doi.org/10.31235/osf.io/u5wba.
  • Turchin, Peter, and Sergey A. Nefedov. 2009. Secular Cycles.
  • Turchin, Peter, Harvey Whitehouse, Pieter François, Daniel Hoyer, Abel Alves, John Baines, David Baker, et al. 2018. “An Introduction to Seshat: Global History Databank.” Journal of Cognitive Historiography 5 (1–2): 115–23. https://doi.org/10.1558/jch.39395.
  • Turchin, Peter, Harvey Whitehouse, Pieter François, Daniel Hoyer, Selin Nugent, Jennifer Larson, Alan Covey, et al. 2019. “Explaining the Rise of Moralizing Religions: A Test of Competing Hypotheses Using the Seshat Databank.” Preprint. SocArXiv. https://doi.org/10.31235/osf.io/2v59j.
  • Whitehouse, H., P. Francois, J. G. Manning, R. Brennan, T. Currie, K. Feeney, and P. Turchin. 2016. “A Macroscope for Global History - Seshat Global History Databank: A Methodological Overview.” Digital Humanities Quarterly. https://ora.ox.ac.uk/objects/uuid:5b10c64e-51ae-4ba0-8766-a1bea932c805.
  • Whitehouse, Harvey, and Jonathan A. Lanman. 2014. “The Ties That Bind Us: Ritual, Fusion, and Identification.” Current Anthropology 55 (6): 674–95. https://doi.org/10.1086/678698.
  • Wilson, David Sloan, Elinor Ostrom, and Michael E. Cox. 2013. “Generalizing the Core Design Principles for the Efficacy of Groups.” Journal of Economic Behavior & Organization, Evolution as a General Theoretical Framework for Economics and Public Policy, 90 (June): S21–32. https://doi.org/10.1016/j.jebo.2012.12.010.Wilson, David Sloan, Mark Van Vugt, and Rick O’Gorman. 2008. “Multilevel Selection Theory and Major Evolutionary Transitions: Implications for Psychological Science.” Current Directions in Psychological Science 17 (1): 6–9. https://doi.org/10.1111/j.1467-8721.2008.00538.x.
  • Wrangham, Richard W. 2019. “Hypotheses for the Evolution of Reduced Reactive Aggression in the Context of Human Self-Domestication.” Frontiers in Psychology 10 (August). https://doi.org/10.3389/fpsyg.2019.01914.

This article was updated on November 4, 2022