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As observed in recent centuries, the contemporary variety of kinship systems reflects millennia of human migration, cultural inheritance, adaptation, and diversification. This review describes key developments in prehistoric kinship, from matricentric hominin evolution to the Neolithic transition to agriculture and the heterogeneous resilience of matriliny. Starting with our hominin ancestors, kinship evolved among a cooperative breeding species to multilevel group structure among human hunter-gatherers, to substantial kinship changes brought on by the origins of intensified farming, to permanent settlements and unequal resource access. This review takes the approach that new forms of subsistence facilitated new equations of reproductive success, which changed cultural norms of kinship systems and heritable wealth. Subsequently, the formation of complex societies diminished kinship as the primary organizing principle of society. The article describes new methodologies and theoretical developments, along with critiques of bioarchaeological interpretations of prehistoric kinship.

Economic, social and political inequality between different identity groups is an important contributor to violent conflicts within societies. To deepen our understanding of the underlying social dynamics, we develop a mathematical model describing cooperation and conflict in a society composed of multiple factions engaged in economic and political interactions. Our model predicts that growing economic and political inequality tends to lead to the collapse of cooperation between factions that were initially seeking to cooperate. Certain mechanisms can delay this process, including the decoupling of political and economic power through rule of law and allegiance to the state or dominant faction. Counterintuitively, anti-conformity (a social norm for independent action) can also stabilize society, by preventing initial defections from cooperation from cascading through society. However, the availability of certain material resources that can be acquired by the state without cooperation with other factions has the opposite effect. We test several of these predictions using a multivariate statistical analysis of data covering 75 countries worldwide. Using social unrest as a proxy for the breakdown of cooperation in society, we find support for many of the predictions from our theory.

Cumulative cultural evolution (CCE) occurs among humans who may be presented with many similar options from which to choose, as well as many social influences and diverse environments. It is unknown what general principles underlie the wide range of CCE dynamics and whether they can all be explained by the same unified paradigm. Here, we present a scalable evolutionary model of discrete choice with social learning, based on a few behavioural science assumptions. This paradigm connects the degree of transparency in social learning to the human tendency to imitate others. Computer simulations and quantitative analysis show the interaction of three primary factors—information transparency, popularity bias and population size—drives the pace of CCE. The model predicts a stable rate of evolutionary change for modest degrees of popularity bias. As popularity bias grows, the transition from gradual to punctuated change occurs, with maladaptive subpopulations arising on their own. When the popularity bias gets too severe, CCE stops. This provides a consistent framework for explaining the rich and complex adaptive dynamics taking place in the real world, such as modern digital media., B.V. is supported through the 2020–2021 Biodiversa and Water JPI joint call under the BiodivRestore ERA-NET Cofund (grant no. 101003777) project MPA4Sustainability with funding organizations: Innovation Fund Denmark (IFD), Agence Nationale de la Recherche (ANR), Fundação para a Ciência e a Tecnologia (FCT), Swedish Environmental Protection Agency (SEPA) and grant no. PCI2022-132936 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. S.V. is supported by the Spanish Ministry of Science and Innovation through the State Research Agency (AEI), grant no. PID2020-117822GB-I00/AEI/10.13039/501100011033. We acknowledge the support of the network PIE-202120E047- Conexiones-Life.

Contemporary research on human sociality is heavily influenced by the social identity approach, positioning social categorization as the primary mechanism governing social life. Building on the distinction between agency and identity in the individual self (“I” vs. “Me”), we emphasize the analogous importance of distinguishing collective agency from collective identity (“We” vs. “Us”). While collective identity is anchored in the unique characteristics of group members, collective agency involves the adoption of a shared subjectivity that is directed toward some object of our attention, desire, emotion, belief, or action. These distinct components of the collective self are differentiated in terms of their mental representations, neurocognitive underpinnings, conditions of emergence, mechanisms of social convergence, and functional consequences. Overall, we show that collective agency provides a useful complement to the social categorization approach, with unique implications for multiple domains of human social life, including collective action, responsibility, dignity, violence, dominance, ritual, and morality.

Agencies reporting on disease outbreaks face many choices about what to report and the scale of its dissemination. Reporting impacts an epidemic by influencing individual decisions directly, and the social network in which they are made. We simulated a dynamic multiplex network model-with coupled infection and communication layers-to examine behavioral impacts from the nature and scale of epidemiological information reporting. We explored how adherence to protective behaviors (social distancing) can be facilitated through epidemiological reporting, social construction of perceived risk, and local monitoring of direct connections, but eroded via social reassurance. We varied reported information (total active cases, daily new cases, hospitalizations, hospital capacity exceeded, or deaths) at one of two scales (population level or community level). Total active and new case reporting at the population level were the most effective approaches, relative to the other reporting approaches. Case reporting, which synergizes with test-trace-and-isolate and vaccination policies, should remain a priority throughout an epidemic.

The explosion of online knowledge has made knowledge, paradoxically, difficult to find. A web or journal search might retrieve thousands of articles, ranked in a manner that is biased by, for example, popularity or eigenvalue centrality rather than by informed relevance to the complex query. With hundreds of thousands of articles published each year, the dense, tangled thicket of knowledge grows even more entwined. Although natural language processing and new methods of generating knowledge graphs can extract increasingly high-level interpretations from research articles, the results are inevitably biased toward recent, popular, and/or prestigious sources. This is a result of the inherent nature of human social-learning processes. To preserve and even rediscover lost scientific ideas, we employ the theory that scientific progress is punctuated by means of inspired, revolutionary ideas at the origin of new paradigms. Using a brief case example, we suggest how phylogenetic inference might be used to rediscover potentially useful lost discoveries, as a way in which machines could help drive revolutionary science.

This study investigates how social organization and mobility changed during the Neolithic Demographic Transition (NDT) in northern Vietnam. Dental nonmetric traits were assessed for pre-Neolithic Con Co Ngua (early seventh millennium BP; n = 38) and Neolithic Man Bac (c. 3800–3600 BP; n = 65), along with cranial nonmetric data for the same Man Bac individuals. It identifies five putative kin lineages for Con Co Ngua and six for Man Bac, with little evidence for spatial organization by lineage in either cemetery. The mean 87Sr/86Sr for Con Co Ngua was 0.70947 ± 0.00017 (n = 40), and for Man Bac 0.70927 ± 0.00055 (n = 27). Man Bac had more variance in overall 87Sr/86Sr, but Man Bac females showed lower variance and a different mean than males within three of the putative lineages identified. While this may signal the presence of uxorilocal postmarital residence at Man Bac, overall, we find no evidence for a marked change in social organization.

The sharp distinction between biological traits and culturally based traits, which had long been standard in evolutionary approaches to behavior, was blurred in the early 1980s by mathematical models that allowed a co-dependent evolution of genetic transmission and cultural information. Niche-construction theory has since added another contrast to standard evolutionary theory, in that it views niche construction as a cause of evolutionary change rather than simply a product of selection. While offering a new understanding of the coevolution of genes, culture, and human behavior, niche-construction models also invoke multivariate causality, which require multiple time series to resolve. The empirical challenge lies in obtaining time-series data on causal pathways involved in the coevolution of genes, culture, and behavior. This is a significant issue in archeology, where time series are often sparse and causal behaviors are represented only by proxies in the material record.

National democracy is a rare thing in human history and its stability has long been tied to the cultural values of citizens. Yet it has not been established whether changing cultural values made modern democracy possible or whether those values were a response to democratic institutions. Here we combine longitudinal data and cohort information of nearly 500,000 individuals from 109 nations to track the co-evolution of democratic values and institutions over the last century. We find that cultural values of openness towards diversity predict a shift towards democracy and that nations with low institutional confidence are prone to political instability. In addition, the presence of democratic institutions did not predict any substantive changes in the measured cultural values. These results hold accounting for other factors, including gross domestic product per capita and non-independence between nations due to shared cultural ancestry. Cultural values lead to, rather than follow, the emergence of democracy. This indicates that current stable democracies will be under threat, should cultural values of openness to diversity and institutional confidence substantially decline.

From a gene-culture evolutionary perspective, the recent rise in obesity rates around the Developed world is unprecedented; perhaps the most rapid population-scale shift in human phenotype ever to occur. Focusing on the recent rise of obesity and diabetes in the United States, we consider the predictions of human behavioral ecology (HBE) versus the predictions of social learning (SL) of obesity through cultural traditions and/or peer–to–peer influence. To isolate differences that might discriminate these different models, we first explore temporal and geographic trends in the inverse correlation between household income and obesity and diabetes rates in the U.S. Whereas by 2015 these inverse correlations were strong, these correlations were non-existent as recently as 1990. The inverse correlations have evolved steadily over recent decades, and we present equations for their time evolution since 1990. We then explore evidence for a “social multiplier” effect at county scale over a ten-year period, as well as a social diffusion pattern at state scale over a 26–year period. We conclude that these patterns support HBE and SL as factors driving obesity, with HBE explaining ultimate causation. As a specific “ecological” driver for this human behavior, we speculate that refined sugar in processed foods may be a prime driver of increasing obesity and diabetes.

National responses to a pandemic require populations to comply through personal behaviors that occur in a cultural context. Here we show that aggregated cultural values of nations, derived from World Values Survey data, have been at least as important as top-down government actions in predicting the impact of COVID-19. At the population level, the cultural factor of cosmopolitanism, together with obesity, predict higher numbers of deaths in the first two months of COVID-19 on the scale of nations. At the state level, the complementary variables of government efficiency and public trust in institutions predict lower death numbers. The difference in effect between individual beliefs and behaviors, versus state-level actions, suggests that open cosmopolitan societies may face greater challenges in limiting a future pandemic or other event requiring a coordinated national response among the population. More generally, mass cultural values should be considered in crisis preparations. Supplementary Information The online version contains supplementary material available at 10.1007/s43545-021-00080-2.

Analysts of social media differ in their emphasis on the effects of message content versus social network structure. The balance of these factors may change substantially across time. When a major event occurs, initial independent reactions may give way to more social diffusion of interpretations of the event among different communities, including those committed to disinformation. Here, we explore these dynamics through a case study analysis of the Russian-language Twitter content emerging from Belarus before and after its presidential election of August 9, 2020. From these Russian-language tweets, we extracted a set of topics that characterize the social media data and construct networks to represent the sharing of these topics before and after the election. The case study in Belarus reveals how misinformation can be re-invigorated in discourse through the novelty of a major event. More generally, it suggests how audience networks can shift from influentials dispensing information before an event to a de-centralized sharing of information after it.The online version contains supplementary material available at 10.1007/s43545-022-00330-x.

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Decisions to adhere to health-protective behaviors (e.g. mask-wearing, social distancing, etc.) that impact the spread of COVID-19 are not made in isolation by each individual. They are instead the result of the social construction of perceived risks and resulting community norms. In populations in which disease is unlikely to spread throughout all communities simultaneously, community-driven perception of risk can drastically alter collective outcomes. A community could respond to a few infections by becoming fearful and adopting anticipatory behaviors that protect them from disease spread. Similarly, there could be false reassurance, in which low disease incidence over time leads to community consensus that protective actions are unnecessary (even if they are the reason cases remains rare). We therefore model COVID-19 spread with three synergistic dynamics governing individual behavioral choices: (1) Social construction of concern, (2) Awareness of disease incidence, and (3) Reassurance by lack of disease. We use a multiplex network approach that captures social communication and epidemiological spread. We find that effective protective policies enacted too early may backfire by allowing a community to become reassured and therefore unwilling to adopt or maintain further protective behaviors. Based on these insights, we propose that public health policies for which success relies on collective action should be designed to exploit thebehaviourally receptive phase; the period between the generation of sufficient concern as to foster adoption of novel protective behaviors and the relaxation of adherence driven by reassurance fostered by avoidance of negative outcomes over time.

The study of observational learning, or learning from others, is a cornerstone of the behavioral sciences, because it grounds the continuity, diversity, and innovation inherent to humanity's cultural repertoire within the social learning capacities of individual humans. In contrast, collective learning, or learning with others, has been underappreciated in terms of its importance to human cognition, cohesion, and culture. We offer a theory of collective learning, wherein the cognitive capacity of collective attention indicates and represents common knowledge across group members, yielding mutually known representations, emotions, evaluations, and beliefs. By enhancing the comprehension of and cohesion with fellow group members, collective attention facilitates communication, remembering, and problem-solving in human groups. We also discuss the implications of collective learning theory for the development of collective identities, social norms, and strategic cooperation. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

We agree that the emergence of cumulative technological culture was tied to nonsocial cognitive skills, namely, technical-reasoning skills, which allowed humans to constantly acquire and improve information. Our concern is with a reading of the history of cumulative technological culture that is based largely on modern experiments in simulated settings and less on phenomena crucial to the long-term dynamics of cultural evolution.

Being able to identify individual populations has long been of interest in archaeology, but within the last several decades it has become a specific focus as researchers have linked evolution-based theoretical models of cultural transmission with innovative analytical methods to better understand how groups of agents use culturally acquired information to navigate across fitness landscapes. Other animals learn, but humans have the unique ability to accumulate learned information rapidly and to pass it on to future generations. Nowhere is this interest in applying models of cultural transmission more evident than in the archaeology of the late Pleistocene colonization of North America, where researchers are beginning to identify distinct populations and to trace their movements across complex physical and cultural landscapes.

Suppementary methods and results for the paper “Cultural prerequistes of socioeconomic development”

As adaptive systems, kinship and its accompanying rules have co-evolved with elements of complex societies, including wealth inheritance, subsistence, and power relations. Here we consider an aspect of kinship evolution in the Austronesian dispersal that began from about 5500 BP in Taiwan, reaching Melanesia about 3200 BP, and dispersing into Micronesia by 1500 BP. Previous, foundational work has used phylogenetic comparative methods and ethnolinguistic information to infer matrilocal residence in proto-Austronesian societies. Here we apply Bayesian phylogenetic analyses to a data set on Austronesian societies that combines existing data on marital residence systems with a new set of ethnographic data, introduced here, on initiation rites. Transition likelihoods between cultural-trait combinations were modeled on an ensemble of 1000 possible Austronesian language trees, using Reversible Jump Markov Chain Monte Carlo (RJ-MCMC) simulations. Compared against a baseline phylogenetic model of independent evolution, a phylogenetic model of correlated evolution between female and male initiation rites is substantially more likely (log Bayes factor: 17.9). This indicates, over the generations of Austronesian dispersal, initiation rites were culturally stable when both female and male rites were in the same state (both present or both absent), yet relatively unstable for female-only rites. The results indicate correlated phylogeographic evolution of cultural initiation rites in the prehistoric dispersal of Austronesian societies across the Pacific. Once acquired, male initiation rites were more resilient than female-only rites among Austronesian societies.

In this paper we respond to the useful comments made by J. J. Bissell 2017, on our paper Garnett et al 2015. We use this opportunity to explain in more detail our use of agent based modelling of historical processes, and how it can raise interesting and thought provoking questions that could be answered by additional historical research. In this case, questions around the possible relationship with the size of the British banking sector and the formation of new banks. We also take the opportunity to present further data on on the possible reasons for the rise and fall in the population of British banks, and suggest that the 'tipping point' might not have been such a radical change.