Evidence of direct and indirect reciprocity in network-structured economic games.

Formal theoretical models propose that cooperative networks can be maintained when individuals condition behavior on social standing. Here, we empirically examine the predictions of such models of positive and negative indirect reciprocity using a suite of network-structured economic games in four rural Colombian communities (Nind = 496 individuals, Nobs = 53,876 ratings/transfers). We observe that, at a dyadic-level, individuals have a strong tendency to exploit and punish others in bad standing (e.g., those perceived as selfish), and allocate resources to those in good standing (e.g., those perceived as generous). These dyadic findings scale to a more generalized, community level, where reputations for being generous are associated with receipt of allocations, and reputations for being selfish are associated with receipt of punishment. These empirical results illustrate the roles that both positive and negative reciprocity, and costly punishment, play in sustaining community-wide cooperation networks.

Women's subsistence networks scaffold cultural transmission among BaYaka foragers in the Congo Basin.

In hunter-gatherer societies, women's subsistence activities are crucial for food provisioning and children's social learning but are understudied relative to men's activities. To understand the structure of women's foraging networks, we present 230 days of focal-follow data in a BaYaka community. To analyze these data, we develop a stochastic blockmodel for repeat observations with uneven sampling. We find that women's subsistence networks are characterized by cooperation between kin, gender homophily, and mixed age-group composition. During early childhood, individuals preferentially coforage with adult kin, but those in middle childhood and adolescence are likely to coforage with nonkin peers, providing opportunities for horizontal learning. By quantifying the probability of coforaging ties across age classes and relatedness levels, our findings provide insights into the scope for social learning during women's subsistence activities in a real-world foraging population and provide ground-truth values for key parameters used in formal models of cumulative culture.

Modelling animal network data in R using STRAND.

There have been recent calls for wider application of generative modelling approaches in applied social network analysis. At present, however, it remains difficult for typical end users-for example, field researchers-to implement generative network models, as there is a dearth of openly available software packages that make application of such models as simple as other, permutation-based approaches. Here, we outline the STRAND R package, which provides a suite of generative models for Bayesian analysis of animal social network data that can be implemented using simple, base R syntax. To facilitate ease of use, we provide a tutorial demonstrating how STRAND can be used to model proportion, count or binary network data using stochastic block models, social relation models or a combination of the two modelling frameworks. STRAND facilitates the application of generative network models to a broad range of data found in the animal social networks literature.

The interdependence of relational and material wealth inequality in Pemba, Zanzibar.

The extent of inequality in material wealth across different types of societies is well established. Less clear, however, is how material wealth is associated with relational wealth, and the implications of such associations for material wealth inequality. Theory and evidence suggest that material wealth both guides, and is patterned by, relational wealth. While existing comparative studies typically assume complementarity between different types of wealth, such associations may differ for distinct kinds of relational wealth. Here, we first review the literature to identify how and why different forms of relational wealth may align. We then turn to an analysis of household-level social networks (food sharing, gender-specific friendship and gender-specific co-working networks) and material wealth data from a rural community in Pemba, Zanzibar. We find that (i) the materially wealthy have most relational ties, (ii) the associations between relational and material wealth-as well as relational wealth more generally-are patterned by gender differences, and (iii) different forms of relational wealth have similar structural properties and are closely aligned. More broadly, we show how examining the patterning of distinct types of relational wealth provides insights into how and why inequality in material wealth remains muted in a community undergoing rapid economic change. This article is part of the theme issue 'Evolutionary ecology of inequality'.

Reproductive inequality in humans and other mammals.

To address claims of human exceptionalism, we determine where humans fit within the greater mammalian distribution of reproductive inequality. We show that humans exhibit lower reproductive skew (i.e., inequality in the number of surviving offspring) among males and smaller sex differences in reproductive skew than most other mammals, while nevertheless falling within the mammalian range. Additionally, female reproductive skew is higher in polygynous human populations than in polygynous nonhumans mammals on average. This patterning of skew can be attributed in part to the prevalence of monogamy in humans compared to the predominance of polygyny in nonhuman mammals, to the limited degree of polygyny in the human societies that practice it, and to the importance of unequally held rival resources to women's fitness. The muted reproductive inequality observed in humans appears to be linked to several unusual characteristics of our species-including high levels of cooperation among males, high dependence on unequally held rival resources, complementarities between maternal and paternal investment, as well as social and legal institutions that enforce monogamous norms.

Reliable network inference from unreliable data: A tutorial on latent network modeling using STRAND.

Social network analysis provides an important framework for studying the causes, consequences, and structure of social ties. However, standard self-report measures-for example, as collected through the popular "name-generator" method-do not provide an impartial representation of such ties, be they transfers, interactions, or social relationships. At best, they represent perceptions filtered through the cognitive biases of respondents. Individuals may, for example, report transfers that did not really occur, or forget to mention transfers that really did. The propensity to make such reporting inaccuracies is both an individual-level and item-level characteristic-variable across members of any given group. Past research has highlighted that many network-level properties are highly sensitive to such reporting inaccuracies. However, there remains a dearth of easily deployed statistical tools that account for such biases. To address this issue, we provide a latent network model that allows researchers to jointly estimate parameters measuring both reporting biases and a latent, underlying social network. Building upon past research, we conduct several simulation experiments in which network data are subject to various reporting biases, and find that these reporting biases strongly impact fundamental network properties. These impacts are not adequately remedied using the most frequently deployed approaches for network reconstruction in the social sciences (i.e., treating either the union or the intersection of double-sampled data as the true network), but are appropriately resolved through the use of our latent network models. To make implementation of our models easier for end-users, we provide a fully documented R package, STRAND, and include a tutorial illustrating its functionality when applied to empirical food/money sharing data from a rural Colombian population. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Towards a computational network theory of social groups.

Network theory is necessary for the realization of cognitive representations and resulting empirical observations of social groups. We propose that the triadic primitives denoting individual roles are multilayer, with positive and negative relations feeding into cost-benefit calculations. Through this, we advance a computational theory that generalizes to different scales and to contexts where conflict is not present.

Political Alliance Formation and Cooperation Networks in the Utah State Legislature.

Social network analysis has become an increasingly important tool among political scientists for understanding legislative cooperation in modern, democratic nation-states. Recent research has demonstrated the influence that group affinity (homophily) and mutual exchanges (reciprocity) have in structuring political relationships. However, this literature has typically focused on political cooperation where costs are low, relationships are not exclusive, and/or partisan competition is high. Patterns of legislative behavior in alternative contexts are less clear and remain largely unexamined. Here, we compare theoretical expectations of cooperation in these contexts from the political and biosocial sciences and implement the first assessment of political alliance formation in a novel legislative environment where costs to cooperation are high and party salience low. We implement a stochastic actor-oriented model (SAOM) to examine bill floor sponsorship, a process in which a "floor sponsor" becomes the exclusive advocate for a colleague's piece of legislation, in the Utah state legislature from 2005 to 2008-a context in which gender (male) and political party (Republican) supermajorities exist. We find that (1) party and gender homophily predict who legislators recruit as floor sponsors, whereas seniority does not, and (2) legislators frequently engage in reciprocal exchanges of floor sponsorship. In addition, whereas gender homophily increases the likelihood of reciprocity, party homophily decreases it. Our findings suggest that when the cost of cooperation is high, political actors use in-group characteristics for initiating alliances, but once a cooperative relationship is established with an out-group political member, it is reinforced through repeated exchanges. These findings may be useful for understanding the rise of political polarization and gridlock in democracies internationally.

Social hierarchies and social networks in humans.

Across species, social hierarchies are often governed by dominance relations. In humans, where there are multiple culturally valued axes of distinction, social hierarchies can take a variety of forms and need not rest on dominance relations. Consequently, humans navigate multiple domains of status, i.e. relative standing. Importantly, while these hierarchies may be constructed from dyadic interactions, they are often more fundamentally guided by subjective peer evaluations and group perceptions. Researchers have typically focused on the distinct elements that shape individuals' relative standing, with some emphasizing individual-level attributes and others outlining emergent macro-level structural outcomes. Here, we synthesize work across the social sciences to suggest that the dynamic interplay between individual-level and meso-level properties of the social networks in which individuals are embedded are crucial for understanding the diverse processes of status differentiation across groups. More specifically, we observe that humans not only navigate multiple social hierarchies at any given time but also simultaneously operate within multiple, overlapping social networks. There are important dynamic feedbacks between social hierarchies and the characteristics of social networks, as the types of social relationships, their structural properties, and the relative position of individuals within them both influence and are influenced by status differentiation. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.

DieTryin: An R package for data collection, automated data entry, and post-processing of network-structured economic games, social networks, and other roster-based dyadic data.

Researchers studying social networks and inter-personal sentiments in bounded or small-scale communities face a trade-off between the use of roster-based and free-recall/name-generator-based survey tools. Roster-based methods scale poorly with sample size, and can more easily lead to respondent fatigue; however, they generally yield higher quality data that are less susceptible to recall bias and that require less post-processing. Name-generator-based methods, in contrast, scale well with sample size and are less likely to lead to respondent fatigue. However, they may be more sensitive to recall bias, and they entail a large amount of highly error-prone post-processing after data collection in order to link elicited names to unique identifiers. Here, we introduce an R package, DieTryin, that allows for roster-based dyadic data to be collected and entered as rapidly as name-generator-based data; DieTryin can be used to run network-structured economic games, as well as collect and process standard social network data and round-robin Likert-scale peer ratings. DieTryin automates photograph standardization, survey tool compilation, and data entry. We present a complete methodological workflow using DieTryin to teach end-users its full functionality.

Coalitions and conflict: A longitudinal analysis of men's politics.

To negotiate conflict and navigate status hierarchy, individuals in many species form coalitions. We describe inter-personal conflicts and assess theories of coalition formation in a small-scale human society. Based on longitudinal and cross-sectional social network analysis of men in two communities of Tsimane forager-horticulturalists, we find evidence of reciprocity in coalitional support, as well as evidence of transitivity: an ally of my ally is likely to become my ally. We find mixed support for coalition formation between individuals who share a common adversary. Coalition formation was also predicted by food- and labour-sharing and especially by kinship. Physically formidable men and men higher in informal status were more likely to provide coalitional support over time; evidence was mixed that they receive more coalitional support. The highest status men are hubs of a dense coalitional support network that indirectly link all men in the community. These findings suggest that male coalition formation is multiply motivated, and in general reveals the political dynamics that structure men's lives in small, relatively egalitarian communities.

The dynamics of men's cooperation and social status in a small-scale society.

We propose that networks of cooperation and allocation of social status co-emerge in human groups. We substantiate this hypothesis with one of the first longitudinal studies of cooperation in a preindustrial society, spanning 8 years. Using longitudinal social network analysis of cooperation among men, we find large effects of kinship, reciprocity and transitivity in the nomination of cooperation partners over time. Independent of these effects, we show that (i) higher-status individuals gain more cooperation partners, and (ii) individuals gain status by cooperating with individuals of higher status than themselves. We posit that human hierarchies are more egalitarian relative to other primates species, owing in part to greater interdependence between cooperation and status hierarchy.