Social hierarchies and social networks in humans

Social structure and the evolutionary ecology of inequality

From rising disparities in income to limited socio-political representation for minority groups, inequality is a topic of perennial interest for contemporary society. Research in the evolutionary sciences has started to investigate how social structure allows inequality to evolve, but is developing in silo from existing work in the social and cognitive sciences. I synthesise these literatures to present a theoretical framework of how and why cultural and ecological conditions can create social structure that either produces or constrains inequality. According to this framework, such conditions dictate the costs and benefits of cooperation that shape individuals' social preferences and resulting behaviours. These behaviours aggregate to produce distinct structures of a society's social networks, which generate different levels of inequality observed across societies.

The ecology of ageing in wild societies: linking age structure and social behaviour

The age of individuals has consequences not only for their fitness and behaviour but also for the functioning of the groups they form. Because social behaviour often changes with age, population age structure is expected to shape the social organization, the social environments individuals experience and the operation of social processes within populations. Although research has explored changes in individual social behaviour with age, particularly in controlled settings, there is limited understanding of how age structure governs sociality in wild populations. Here, we synthesize previous research into age-related effects on social processes in natural populations, and discuss the links between age structure, sociality and ecology, specifically focusing on how population age structure might influence social structure and functioning. We highlight the potential for using empirical data from natural populations in combination with social network approaches to uncover pathways linking individual social ageing, population age structure and societal functioning. We discuss the broader implications of these insights for understanding the social impacts of anthropogenic effects on animal population demography and for building a deeper understanding of societal ageing in general.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.

A gene-culture co-evolutionary perspective on the puzzle of human twinship

Natural selection should favour litter sizes that optimise trade-offs between brood-size and offspring viability. Across the primate order, the modal litter size is one, suggesting a deep history of selection favouring minimal litters in primates. Humans, however - despite having the longest juvenile period and slowest life-history of all primates - still produce twin births at appreciable rates, even though such births are costly. This presents an evolutionary puzzle. Why is twinning still expressed in humans despite its cost? More puzzling still is the discordance between the principal explanations for human twinning and extant empirical data. Such explanations propose that twinning is regulated by phenotypic plasticity in polyovulation, permitting the production of larger sib sets if and when resources are abundant. However, comparative data suggest that twinning rates are actually highest in poorer economies and lowest in richer, more developed economies. We propose that a historical dynamic of gene-culture co-evolution might better explain this geographic patterning. Our explanation distinguishes geminophilous and geminophobic cultural contexts, as those celebrating twins (e.g. through material support) and those hostile to twins (e.g. through sanction of twin-infanticide). Geminophilous institutions, in particular, may buffer the fitness cost associated with twinning, potentially reducing selection pressures against polyovulation. We conclude by synthesising a mathematical and empirical research programme that might test our ideas.

Goerlich K. Increased sensitivity to social hierarchy during social competition versus cooperation

Social hierarchy is a typical feature of social organization. The ability to quickly recognize social hierarchy information is crucial for adapting to social contexts. Here, we adopted fast periodic visual stimulation with electroencephalography to assess the neural responses to social hierarchy during social competition and cooperation, respectively. Participants first learned hierarchical faces from a competitive game versus a cooperative game. We then sequentially presented the learned hierarchical faces with a specific frequency in a set of faces. Results showed that participants rated the inferior player as lower in the social hierarchy in the cooperative context compared to the competitive context, indicating that social context affects the judgment of others' rank. Moreover, higher neural responses to high and low-hierarchy faces versus medium-hierarchy faces were observed, suggesting rapid discrimination of social hierarchy from faces. Interestingly, rank-specific neural responses were more pronounced in the competitive context than in the cooperative context, indicating increased sensitivity to social hierarchy during social competition versus social cooperation. This study provides behavioral and neural evidence for rapid, automatic processing of social hierarchy information and for an increased sensitivity to such information in competitive versus cooperative social contexts.

Connecting and integrating cooperation within and between species

There has long been a fundamental divide in the study of cooperation: researchers focus either on cooperation within species, including but not limited to sociality, or else on cooperation between species, commonly termed mutualism. Here, we explore the ecologically and evolutionarily significant ways in which within- and between-species cooperation interact. We highlight two primary cross-linkages. First, cooperation of one type can change the context in which cooperation of the other type functions, and thus potentially its outcome. We delineate three possibilities: (i) within-species cooperation modulates benefits for a heterospecific partner; (ii) between-species cooperation affects the dynamics of within-species cooperation; and (iii) both processes take place interactively. The second type of cross-linkage emerges when resources or services that cooperation makes available are obtainable either from members of the same species or from different species. This brings cooperation at the two levels into direct interaction, to some extent obscuring the distinction between them. We expand on these intersections between within- and between-species cooperation in a diversity of taxa and interaction types. These interactions have the potential to weave together social networks and trophic dynamics, contributing to the structure and functioning of ecological communities in ways that are just beginning to be explored. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Behavioral and neural responses to social exclusion in women: the role of facial attractiveness and friendliness

The behavioral and neural responses to social exclusion were examined in women randomized to four conditions, varying in levels of attractiveness and friendliness. Informed by evolutionary theory, we predicted that being socially excluded by attractive unfriendly women would be more distressing than being excluded by unattractive women, irrespective of their friendliness level. Our results contradicted most of our predictions but provide important insights into women's responses to interpersonal conflict. Accounting for rejection sensitivity, P300 event-related potential amplitudes were largest when women were excluded by unattractive unfriendly women. This may be due to an expectancy violation or an annoyance with being excluded by women low on social desirability. An examination of anger rumination rates by condition suggests the latter. Only attractive women's attractiveness ratings were lowered in the unfriendly condition, indicating they were specifically punished for their exclusionary behavior. Women were more likely to select attractive women to compete against with one exception-they selected the Black attractive opponent less often than the White attractive opponent when presented as unfriendly. Finally, consistent with studies on retaliation in relation to social exclusion, women tended to rate competitors who rejected them as being more rude, more competitive, less attractive, less nice, and less happy than non-competitors. The ubiquity of social exclusion and its pointed emotional and physiological impact on women demands more research on this topic.

Fast meta-analytic approximations for relational event models: applications to data streams and multilevel data

Large relational-event history data stemming from large networks are becoming increasingly available due to recent technological developments (e.g. digital communication, online databases, etc). This opens many new doors to learn about complex interaction behavior between actors in temporal social networks. The relational event model has become the gold standard for relational event history analysis. Currently, however, the main bottleneck to fit relational events models is of computational nature in the form of memory storage limitations and computational complexity. Relational event models are therefore mainly used for relatively small data sets while larger, more interesting datasets, including multilevel data structures and relational event data streams, cannot be analyzed on standard desktop computers. This paper addresses this problem by developing approximation algorithms based on meta-analysis methods that can fit relational event models significantly faster while avoiding the computational issues. In particular, meta-analytic approximations are proposed for analyzing streams of relational event data, multilevel relational event data and potentially combinations thereof. The accuracy and the statistical properties of the methods are assessed using numerical simulations. Furthermore, real-world data are used to illustrate the potential of the methodology to study social interaction behavior in an organizational network and interaction behavior among political actors. The algorithms are implemented in the publicly available R package 'remx'.

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.

Explainable prediction of node labels in multilayer networks: a case study of turnover prediction in organizations

In real-world classification problems, it is important to build accurate prediction models and provide information that can improve decision-making. Decision-support tools are often based on network models, and this article uses information encoded by social networks to solve the problem of employer turnover. However, understanding the factors behind black-box prediction models can be challenging. Our question was about the predictability of employee turnover, given information from the multilayer network that describes collaborations and perceptions that assess the performance of organizations that indicate the success of cooperation. Our goal was to develop an accurate prediction procedure, preserve the interpretability of the classification, and capture the wide variety of specific reasons that explain positive cases. After a feature engineering, we identified variables with the best predictive power using decision trees and ranked them based on their added value considering their frequent co-occurrence. We applied the Random Forest using the SMOTE balancing technique for prediction. We calculated the SHAP values to identify the variables that contribute the most to individual predictions. As a last step, we clustered the sample based on SHAP values to fine-tune the explanations for quitting due to different background factors.

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.

Higher subjective socioeconomic status is linked to increased charitable giving and mentalizing-related neural value coding

Socioeconomic status (SES), a concept related to an individual's economic and social position relative to others, can shape social interactions like altruistic behaviors. However, little is known about the exact neurocognitive mechanisms that link SES with altruism. Our study aimed to provide a comprehensive account of the sociocognitive and neural mechanisms through which SES affects charitable giving - an important variant of human altruism. To this end, participants completed a charitable donation task while their brain activity was measured using functional magnetic resonance imaging (fMRI). We also assessed participants' socio-cognitive ability to infer other people's mental states (i.e., mentalizing) - a driver of prosocial behavior - in an independent social task. Behaviorally, we found that both charitable giving and social cognition were status-dependent, as subjective SES positively predicted donations and mentalizing capacity. Moreover, the link between SES and charitable giving was mediated by individuals' mentalizing capacity. At the neural level, a multivariate pattern analysis of fMRI data revealed that higher subjective SES was associated with stronger value coding in the right temporoparietal junction (rTPJ). The strength of this value representation predicted charitable giving and was linked to mentalizing. Furthermore, we observed an increased negative functional coupling between rTPJ and left putamen with higher SES. Together, increased charitable giving in higher-status individuals could be explained by status-dependent recruitment of mentalizing-related value coding and altered functional connectivity in the brain. Our findings provide insights into the socio- and neurocognitive mechanisms explaining why and when higher SES leads to prosociality, which might ultimately inform targeted interventions to promote prosocial behavior in human societies.

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'.

The neurobiology of insulin-like growth factor I: From neuroprotection to modulation of brain states

After decades of research in the neurobiology of IGF-I, its role as a prototypical neurotrophic factor is undisputed. However, many of its actions in the adult brain indicate that this growth factor is not only involved in brain development or in the response to injury. Following a three-layer assessment of its role in the central nervous system, we consider that at the cellular level, IGF-I is indeed a bona fide neurotrophic factor, modulating along ontogeny the generation and function of all the major types of brain cells, contributing to sculpt brain architecture and adaptive responses to damage. At the circuit level, IGF-I modulates neuronal excitability and synaptic plasticity at multiple sites, whereas at the system level, IGF-I intervenes in energy allocation, proteostasis, circadian cycles, mood, and cognition. Local and peripheral sources of brain IGF-I input contribute to a spatially restricted, compartmentalized, and timed modulation of brain activity. To better define these variety of actions, we consider IGF-I a modulator of brain states. This definition aims to reconcile all aspects of IGF-I neurobiology, and may provide a new conceptual framework in the design of future research on the actions of this multitasking neuromodulator in the brain.

Human and animal dominance hierarchies show a pyramidal structure guiding adult and infant social inferences

This study investigates the structure of social hierarchies. We hypothesized that if social dominance relations serve to regulate conflicts over resources, then hierarchies should converge towards pyramidal shapes. Structural analyses and simulations confirmed this hypothesis, revealing a triadic-pyramidal motif across human and non-human hierarchies (114 species). Phylogenetic analyses showed that this pyramidal motif is widespread, with little influence of group size or phylogeny. Furthermore, nine experiments conducted in France found that human adults (N = 120) and infants (N = 120) draw inferences about dominance relations that are consistent with hierarchies' pyramidal motif. By contrast, human participants do not draw equivalent inferences based on a tree-shaped pattern with a similar complexity to pyramids. In short, social hierarchies exhibit a pyramidal motif across a wide range of species and environments. From infancy, humans exploit this regularity to draw systematic inferences about unobserved dominance relations, using processes akin to formal reasoning.

Morphine exposure during adolescence induces enduring social changes dependent on adolescent stage of exposure, sex, and social test

Drug exposure during adolescence, when the 'reward' circuitry of the brain is developing, can permanently impact reward-related behavior. Epidemiological studies show that opioid treatment during adolescence, such as pain management for a dental procedure or surgery, increases the incidence of psychiatric illness including substance use disorders. Moreover, the opioid epidemic currently in the United States is affecting younger individuals raising the impetus to understand the pathogenesis of the negative effects of opioids. One reward-related behavior that develops during adolescence is social behavior. We previously demonstrated that social development occurs in rats during sex-specific adolescent periods: early to mid-adolescence in males (postnatal day (P)30-40) and pre-early adolescence in females (P20-30). We thus hypothesized that morphine exposure during the female critical period would result in adult sociability deficits in females, but not males, and morphine administered during the male critical period would result in adult sociability deficits in males, but not females. We found that morphine exposure during the female critical period primarily resulted in deficits in sociability in females, while morphine exposure during the male critical period primarily resulted in deficits in sociability primarily in males. However, depending on the test performed and the social parameter measured, social alterations could be found in both sexes that received morphine exposure at either adolescent stage. These data indicate that when drug exposure occurs during adolescence, and how the endpoint data are measured, will play a large role in determining the effects of drug exposures on social development.

Automatic entry and coding of social networks and dyadic peer ratings

In small-scale communities, social-scientists can use photo-rosters to collect social network and dyadic peer-ratings data. In past work, we introduced an R package to automate photo-standardization, survey construction, and data-entry. This R package, however, lacked two key features required for fully-unsupervised data-entry. First, respondent IDs needed to be manually linked to cellphone photographs of the photo-roster before DieTryin could process the data; second, users needed to identify the locations of the photo-roster in each cellphone photograph using a point-and-click interface. To address the first shortcoming, we introduce a new Android application, DieTryinCam, which facilitates annotation of cell-phone photographs with respondent, question, and panel IDs. To address the second shortcoming, we add new functionality to the DieTryin R package, which allows for the precise location of the photograph roster to be automatically identified. Automated data entry in DieTryin now requires no user input beyond a single function call from R.

Does gender structure social networks across domains of cooperation? An exploration of gendered networks among matrilineal and patrilineal Mosuo

Cooperative networks are essential features of human society. Evolutionary theory hypothesizes that networks are used differently by men and women, yet the bulk of evidence supporting this hypothesis is based on studies conducted in a limited range of contexts and on few domains of cooperation. In this paper, we compare individual-level cooperative networks from two communities in Southwest China that differ systematically in kinship norms and institutions-one matrilineal and one patrilineal-while sharing an ethnic identity. Specifically, we investigate whether network structures differ based on prevailing kinship norms and type of gendered cooperative activity, one woman-centred (preparation of community meals) and one man-centred (farm equipment lending). Our descriptive results show a mixture of 'feminine' and 'masculine' features in all four networks. The matrilineal meals network stands out in terms of high degree skew. Exponential random graph models reveal a stronger role for geographical proximity in patriliny and a limited role of affinal relatedness across all networks. Our results point to the need to consider domains of cooperative activity alongside gender and cultural context to fully understand variation in how women and men leverage social relationships toward different ends. This article is part of the theme issue 'Cooperation among women: evolutionary and cross-cultural perspectives'.

The Island of Female Power? Intersexual Dominance Relationships in the Lemurs of Madagascar

The extant primates of Madagascar (Lemuriformes) represent the endpoints of an adaptive radiation following a single colonization event more than 50 million years ago. They have since evolved a diversity of life history traits, ecological adaptations and social systems that rivals that of all other living primates combined. Their social systems are characterized by a unique combination of traits, including the ability of adult females to dominate adult males. In fact, there is no other group of mammals in which female dominance is so widespread. Yet, recent research has indicated that there is more interspecific variation in lemur intersexual relationships than previously acknowledged. Here, we therefore review and summarize the relevant literature, quantifying the extent of sex-bias in intersexual dominance relations documented in observational and experimental studies in captivity and the wild. Female dominance is often, but not always, implemented by spontaneous male submission in the absence of female aggression and linked to female sexual maturation. We connect the available evidence to the hypotheses that have been proposed to explain the evolution of female dominance among lemurs. The occurrence of female dominance in all lemur families and the interspecific variation in its extent indicate that it has evolved soon after lemurs colonized Madagascar – presumably in response to particular ecological challenges – and that it has since been reduced in magnitude independently in some taxa. Our study contributes important comparative information on sex roles from an independent primate radiation and provides general insights into the conditions, opportunities and obstacles in the evolution of female-biased power.

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.

The dynamics of dominance: open questions, challenges and solutions

Although social hierarchies are recognized as dynamic systems, they are typically treated as static entities for practical reasons. Here, we ask what we can learn from a dynamical view of dominance, and provide a research agenda for the next decades. We identify five broad questions at the individual, dyadic and group levels, exploring the causes and consequences of individual changes in rank, the dynamics underlying dyadic dominance relationships, and the origins and impacts of social instability. Although challenges remain, we propose avenues for overcoming them. We suggest distinguishing between different types of social mobility to provide conceptual clarity about hierarchy dynamics at the individual level, and emphasize the need to explore how these dynamic processes produce dominance trajectories over individual lifespans and impact selection on status-seeking behaviour. At the dyadic level, there is scope for deeper exploration of decision-making processes leading to observed interactions, and how stable but malleable relationships emerge from these interactions. Across scales, model systems where rank is manipulable will be extremely useful for testing hypotheses about dominance dynamics. Long-term individual-based studies will also be critical for understanding the impact of rare events, and for interrogating dynamics that unfold over lifetimes and generations. 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'.

The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies

A century ago, foundational work by Thorleif Schjelderup-Ebbe described a 'pecking order' in chicken societies, where individuals could be ordered according to their ability to exert their influence over their group-mates. Now known as dominance hierarchies, these structures have been shown to influence a plethora of individual characteristics and outcomes, situating dominance research as a pillar of the study of modern social ecology and evolution. Here, we first review some of the major questions that have been answered about dominance hierarchies in the last 100 years. Next, we introduce the contributions to this theme issue and summarize how they provide ongoing insight in the epistemology, physiology and neurobiology, hierarchical structure, and dynamics of dominance. These contributions employ the full range of research approaches available to modern biologists. Cross-cutting themes emerging from these contributions include a focus on cognitive underpinnings of dominance, the application of network-analytical approaches, and the utility of experimental rank manipulations for revealing causal relationships. Reflection on the last 100 years of dominance research reveals how Schjelderup-Ebbe's early ideas and the subsequent research helped drive a shift from an essentialist view of species characteristics to the modern recognition of rich inter-individual variation in social, behavioural and physiological phenotypes. 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'.