Showing papers on "Social dynamics published in 2021"

The importance of individual-to-society feedbacks in animal ecology and evolution.

Abstract: The social decisions that individuals make-who to interact with and how frequently-gives rise to social structure. The resulting social structure then determines how individuals interact with their surroundings-resources and risks, pathogens and predators, competitors and cooperators. However, despite intensive research on (i) how individuals make social decisions and (ii) how social structure shapes social processes (e.g. cooperation, competition and conflict), there are still few studies linking these two perspectives. These perspectives represent two halves of a feedback loop: individual behaviour scales up to define the social environment, and this environment, in turn, feeds back by shaping the selective agents that drive individual behaviour. We first review well-established research areas that have captured both elements of this feedback loop-host-pathogen dynamics and cultural transmission. We then highlight areas where social structure is well studied but the two perspectives remain largely disconnected. Finally, we synthesise existing research on 14 distinct research topics to identify new prospects where the interplay between social structure and social processes are likely to be important but remain largely unexplored. Our review shows that the inherent links between individuals' traits, their social decisions, social structure, and social evolution, warrant more consideration. By mapping the existing and missing connections among many research areas, our review highlights where explicitly considering social structure and the individual-to-society feedbacks can reveal new dimensions to old questions in ecology and evolution.

Temporal properties of higher-order interactions in social networks.

Abstract: Human social interactions in local settings can be experimentally detected by recording the physical proximity and orientation of people Such interactions, approximating face-to-face communications, can be effectively represented as time varying social networks with links being unceasingly created and destroyed over time Traditional analyses of temporal networks have addressed mostly pairwise interactions, where links describe dyadic connections among individuals However, many network dynamics are hardly ascribable to pairwise settings but often comprise larger groups, which are better described by higher-order interactions Here we investigate the higher-order organizations of temporal social networks by analyzing five publicly available datasets collected in different social settings We find that higher-order interactions are ubiquitous and, similarly to their pairwise counterparts, characterized by heterogeneous dynamics, with bursty trains of rapidly recurring higher-order events separated by long periods of inactivity We investigate the evolution and formation of groups by looking at the transition rates between different higher-order structures We find that in more spontaneous social settings, group are characterized by slower formation and disaggregation, while in work settings these phenomena are more abrupt, possibly reflecting pre-organized social dynamics Finally, we observe temporal reinforcement suggesting that the longer a group stays together the higher the probability that the same interaction pattern persist in the future Our findings suggest the importance of considering the higher-order structure of social interactions when investigating human temporal dynamics

Human social sensing is an untapped resource for computational social science

Abstract: The ability to ‘sense’ the social environment and thereby to understand the thoughts and actions of others allows humans to fit into their social worlds, communicate and cooperate, and learn from others’ experiences. Here we argue that, through the lens of computational social science, this ability can be used to advance research into human sociality. When strategically selected to represent a specific population of interest, human social sensors can help to describe and predict societal trends. In addition, their reports of how they experience their social worlds can help to build models of social dynamics that are constrained by the empirical reality of human social systems. The ability of people to understand the thoughts and actions of others—known as social sensing—can be combined with computational social science to advance research into human sociality.

AI as Social Glue: Uncovering the Roles of Deep Generative AI during Social Music Composition

Abstract: Recent advances in deep generative neural networks have made it possible for artificial intelligence to actively collaborate with human beings in co-creating novel content (e.g. music, art). While substantial research focuses on (individual) human-AI collaborations, comparatively less research examines how AI can play a role in human-human collaborations during co-creation. In a qualitative lab study, we observed 30 participants (15 pairs) compose a musical phrase in pairs, both with and without AI. Our findings reveal that AI may play important roles in influencing human social dynamics during creativity, including: 1) implicitly seeding a common ground at the start of collaboration, 2) acting as a psychological safety net in creative risk-taking, 3) providing a force for group progress, 4) mitigating interpersonal stalling and friction, and 5) altering users’ collaborative and creative roles. This work contributes to the future of generative AI in social creativity by providing implications for how AI could enrich, impede, or alter creative social dynamics in the years to come.

Why we should rethink ‘adoption’ in agricultural innovation: Empirical insights from Malawi

Abstract: The challenges of land degradation, climate change and food insecurity have led to the introduction of conservation agriculture (CA) aimed at enhancing yield and soil quality. Despite positive biophysical results, low adoption rates have been the focus of studies identifying constraints to wider uptake. While the adoption framework is popular for measuring agricultural innovation, objective adoption measurements remain problematic and do not recognize the contextual and dynamic decision‐making process. This study uses a technographic and participatory approach to move beyond the adoption framework and understand: (a) how agricultural decision‐making takes place including the knowledge construction, (b) how agriculture is performed in a context of project intervention and (c) how practice adaptation plays out in the context of interacting knowledge. Findings confirm that farmer decision‐making is dynamic, multidimensional and contextual. The common innovation diffusion model uses a theory of change, showcasing benefits through training lead farmers as community advocates and demonstration trials. Our study shows that the assumed model of technology transfer with reference to climate‐smart agriculture interventions is not as linear and effective as assumed previously. We introduce four lenses that contribute to better understanding complex innovation dynamics: (a) social dynamics and information transfer, (b) contextual costs and benefits, (c) experience and risk aversion, and (d) practice adaptation. Investments should build on existing knowledge and farming systems including a focus on the dynamic decision process to support the 'scaling up, scaling out and scaling deep' agenda for sustainable agricultural innovations.

Stochastic social behavior coupled to COVID-19 dynamics leads to waves, plateaus and an endemic state.

Abstract: It is well recognized that population heterogeneity plays an important role in the spread of epidemics. While individual variations in social activity are often assumed to be persistent, i.e. constant in time, here we discuss the consequences of dynamic heterogeneity. By integrating the stochastic dynamics of social activity into traditional epidemiological models we demonstrate the emergence of a new long timescale governing the epidemic, in broad agreement with empirical data. Our Stochastic Social Activity model captures multiple features of real-life epidemics such as COVID-19, including prolonged plateaus and multiple waves, which are transiently suppressed due to the dynamic nature of social activity. The existence of a long timescale due to the interplay between epidemic and social dynamics provides a unifying picture of how a fast-paced epidemic typically will transition to an endemic state.

Stay Connected in An Immersive World: Why Teenagers Engage in Social Virtual Reality

Abstract: Social virtual reality (VR) has emerged as a popular online space for teenagers to interact and socialize. It attracts teens due to the broad range of immersive activities and social engagement opportunities, along with diverse users in terms of age and interest. Yet, little is known about teenagers’ experiences and understandings of this emerging online social space, especially regarding what aspects may attract or dissuade them to social VR. To explore this question, we conducted in-depth interviews with 20 teenagers (e.g., ages 13-18) and reported findings regarding what attracted them to engage in social VR and challenges with social VR that may dissuade them from using it. Our findings contribute to the growing body of scholarship on teenagers’ experiences in emerging, novel online social spaces and highlight potential design implications for creating safer and more fulfilling social VR experiences for teenagers.

No Echo in the Chambers of Political Interactions on Reddit

Abstract: Echo chambers in online social networks, whereby users' beliefs are reinforced by interactions with like-minded peers and insulation from others' points of view, have been decried as a cause of political polarization Here, we investigate their role in the debate around the 2016 US elections on Reddit, a fundamental platform for the success of Donald Trump We identify Trump vs Clinton supporters and reconstruct their political interaction network We observe a preference for cross-cutting political interactions between the two communities rather than within-group interactions, thus contradicting the echo chamber narrative Furthermore, these interactions are asymmetrical: Clinton supporters are particularly eager to answer comments by Trump supporters Beside asymmetric heterophily, users show assortative behavior for activity, and disassortative, asymmetric behavior for popularity Our findings are tested against a null model of random interactions, by using two different approaches: a network rewiring which preserves the activity of nodes, and a logit regression which takes into account possible confounding factors Finally, we explore possible socio-demographic implications Users show a tendency for geographical homophily and a small positive correlation between cross-interactions and voter abstention Our findings shed light on public opinion formation on social media, calling for a better understanding of the social dynamics at play in this context

Religious Affiliation, Daily Spirituals, and Private Religious Factors Promote Marital Commitment Among Married Couples: Does Religiosity Help People Amid the COVID-19 Crisis?

Abstract: Religious studies are a vital branch of social science that seeks to explain the beliefs of human society and deals with the practices and beliefs of individuals. This distinctive study focuses on such influential aspects of a healthy life, which could play a vital role in the marital quality and matrimonial commitment of individuals. The study principally focused on inspecting the role of religiosity in healthy marital commitment among individuals. It is a distinctive and central value in regulating a healthy social life. This research designed a conceptual model for assessing marital commitment, and the study model comprised two primary variables. The study received datasets through a survey questionnaire based on participants from five private and public sectors. The research study conducted an empirical analysis to test the proposed conceptual framework. The findings exhibited that the value of the R 2 model was 0.484, meaning the level of religiosity had a substantial impression on healthy and lasting marital commitment. According to the final outline of the model factors associated with building religious support factors (s = 0.491), the marital commitment had a better and healthier impact. The goodness-of-fit of the measurement of the conceptual model showed a value of 0.51, which indicated that the theoretical model had sufficient consistency and rationality, and accurately fitted the data. Such an advanced statistical model is missing from the previous literature. The study results provide helpful insight to elucidate the social dynamics of marital commitment. The findings designate that religious practices strengthen and promote nuptial commitment. The study is novel in the context of religiosity impact on martial commitment with a cultural background of Pakistan. The generalizability of the study does not apply to the entire population or other regions. Future studies can investigate other religious variables to explore further research findings. The findings are helpful for decision-makers and policymakers to concentrate on marital issues and challenges confronted by couples worldwide.

The effects of circular economy initiative implementation on business performance: the moderating role of organizational culture

Abstract: The study aims to examine the micro-level implications of implementing a circular economy (CE) business model on firms’ financial performance and the effect of organizational culture in this context.,Using a survey method to obtain 617 usable questionnaires from diverse business sectors in Ghana, a largely unexplored region and relying on institutional and legitimacy theories.,The study shows that the implementation of CE policies, such as the reducing, reusing, recycling, recovery and restoration of resources used in manufacturing, distribution and consumption processes, contributes to improved financial efficiency. Furthermore, organizational culture moderates by way of strengthening the positive relationship between CE and business financial performance.,This study contributes to the literature on circularity and the broader discourse on ecological issues by arguing that institutional and legitimacy theories, which are both from the political economy theory, suggest that firms’ economic activities will be influenced by the political, social and institutional context. Therefore, the firm’s decision to embrace a different business model such as CE should be seen from the political environment involving rules and regulations, social dynamics both within and outside the organization and the institutional structures within which the firm operates. These mechanisms establish a business case for the implementation of CE initiatives and is guided by intent and specific goals. This motivates and encourages employees to be more involved in their duties and interactions leading to high levels of employee satisfaction, which improves productivity and profitability.

Taxonomies for structuring models for World-Earth system analysisof the Anthropocene: subsystems, their interactions andsocial-ecological feedback loops

Abstract: . In the Anthropocene, social processes have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling are needed to address these challenges, but the current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth System Models, to hybrid macro-economic Integrated Assessments Models, to a plethora of models of socio-cultural dynamics. World-Earth models, currently not yet available, will need to integrate all these elements, so future World-Earth modellers require a structured approach to identify, classify, select, and combine model components. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by natural laws of physics, chemistry or ecology (i.e., the usual components of Earth system models), (ii) socio-cultural, dominated by processes of human behaviour, decision making and collective social dynamics (e.g., politics, institutions, social networks), and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g., human bodies, natural resource and agriculture). We show how higher-order taxonomies for interactions between two or more subsystems can be derived, highlighting the kinds of social-ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World-Earth system model of socially transmitted discount rates in a greenhouse gas emissions game to illustrate the effects of social-ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World-Earth models for understanding Earth resilience and charting sustainability transitions within planetary boundaries and other future trajectories in the Anthropocene.

Modeling the Social and Spatial Proximity of Crime: Domestic and Sexual Violence Across Neighborhoods.

Abstract: Our goal is to understand the social dynamics affecting domestic and sexual violence in urban areas by investigating the role of connections between area nodes, or communities. We use innovative methods adapted from spatial statistics to investigate the importance of social proximity measured based on connectedness pathways between area nodes. In doing so, we seek to extend the standard treatment in the neighborhoods and crime literature of areas like census blocks as independent analytical units or as interdependent primarily due to geographic proximity. In this paper, we develop techniques to incorporate two types of proximity, geographic proximity and commuting proximity in spatial generalized linear mixed models (SGLMM) in order to estimate domestic and sexual violence in Detroit, Michigan and Arlington County, Virginia. Analyses are based on three types of CAR models (the Besag, York, and Mollie (BYM), Leroux, and the sparse SGLMM models) and two types of SAR models (the spatial lag and spatial error models) to examine how results vary with different model assumptions. We use data from local and federal sources such as the Police Data Initiative and American Community Survey. Analyses show that incorporating information on commuting ties, a non-spatially bounded form of social proximity, to spatial models contributes to better deviance information criteria scores (a metric which explicitly accounts for model fit and complexity) in Arlington for sexual and domestic crime as well as overall crime. In Detroit, the fit is improved only for overall crime. The distinctions in model fit are less pronounced when using cross-validated mean absolute error as a comparison criteria. Overall, the results indicate variations across crime type, urban contexts, and modeling approaches. Nonetheless, in important contexts, commuting ties among neighborhoods are observed to greatly improve our understanding of urban crime. If such ties contribute to the transfer of norms, social support, resources, and behaviors between places, they may then transfer also the effects of crime prevention efforts.

Cognitive Network Science for Understanding Online Social Cognitions: A Brief Review.

Abstract: Social media are digitalizing massive amounts of users' cognitions in terms of timelines and emotional content. Such Big Data opens unprecedented opportunities for investigating cognitive phenomena like perception, personality, and information diffusion but requires suitable interpretable frameworks. Since social media data come from users' minds, worthy candidates for this challenge are cognitive networks, models of cognition giving structure to mental conceptual associations. This work outlines how cognitive network science can open new, quantitative ways for understanding cognition through online media like: (i) reconstructing how users semantically and emotionally frame events with contextual knowledge unavailable to machine learning, (ii) investigating conceptual salience/prominence through knowledge structure in social discourse; (iii) studying users' personality traits like openness-to-experience, curiosity, and creativity through language in posts; (iv) bridging cognitive/emotional content and social dynamics via multilayer networks comparing the mindsets of influencers and followers. These advancements combine cognitive-, network- and computer science to understand cognitive mechanisms in both digital and real-world settings but come with limitations concerning representativeness, individual variability, and data integration. Such aspects are discussed along with the ethical implications of manipulating sociocognitive data. In the future, reading cognitions through networks and social media can expose cognitive biases amplified by online platforms and relevantly inform policy-making, education, and markets about complex cognitive trends.

Discrimination, competitiveness, and support in US graduate student mental health

Abstract: Rising rates of anxiety and depression and the varied costs of these conditions indicate a clear need to create learning environments in which graduate and professional students can more readily thrive. However, the absence of multi-institutional, multi-disciplinary evidence about mental health in graduate education has obscured a clear picture of which populations, contexts and social dynamics merit focused attention and resources. The purpose of this study is therefore to analyze prevalence and risk factors associated with anxiety and depression among a large sample of graduate students, with special attention to how graduate education environments and interactions may be associated with mental health.,This paper offers the first multi-institutional, multi-disciplinary analysis of depression and anxiety among US graduate and professional students. Using a sample of 20,888 students randomly sampled within 69 universities, the author compares depression and anxiety prevalence among fields of study with hierarchical cluster modeling. Then, using a conceptual framework that links social support, role strain and self-determination theories, the author estimates fixed effects multivariate logistic regressions to measure how depression and anxiety are associated with experiencing racial discrimination, support from friends and family, perceived competitiveness in one’s classes, and comfort speaking with one’s professors about mental health.,Graduate students who endure frequent racial discrimination have odds of screening positive for depression and anxiety that are 2.3 and 3.0 times higher, respectively, than those who never experience discrimination. Support from family and friends moderates these relationships and perceived competitiveness exacerbates them. LGBTQ students and students who self-report that finances are a struggle or tight also have higher odds of depression and anxiety. Students in the humanities, arts and architecture have significantly higher prevalence of depression and anxiety than the sample as a whole.,The paper offers broadest base of evidence to date about patterns that are usually experienced at the individual level or analyzed institution-by-institution and field-by-field. Specifically, the author identified social dynamics, fields of study and populations where attention to wellbeing may be especially warranted. The conceptual framework and multivariate results clarify how organizational and individual factors in graduate students’ mental health may be intertwined through competitive, discriminatory, or supportive interactions with peers, faculty, family and friends. Findings clarify a need for awareness of the contexts and interactions that graduate students experience as well as individual factors that are associated with student wellbeing.

Footprints at School: Modelling In-class Social Dynamics from Students’ Physical Positioning Traces

Abstract: Schools are increasingly becoming into complex learning spaces where students interact with various physical and digital resources, educators, and peers. Although the field of learning analytics has advanced in analysing logs captured from digital tools, less progress has been made in understanding the social dynamics that unfold in physical learning spaces. Among the various rapidly emerging sensing technologies, position tracking may hold promises to reveal salient aspects of activities in physical learning spaces such as the formation of interpersonal ties among students. This paper explores how granular x-y physical positioning data can be analysed to model social interactions among students and teachers. We conducted an 8-week longitudinal study in which positioning traces of 98 students and six teachers were automatically captured every day in an open-plan public primary school. Positioning traces were analysed using social network analytics (SNA) to extract a set of metrics to characterise students’ positioning behaviours and social ties at cohort and individual levels. Results illustrate how analysing positioning traces through the lens of SNA can enable the identification of certain pedagogical approaches that may be either promoting or discouraging in-class social interaction, and students who may be socially isolated.

The Social Dynamics of Collective Action: Evidence from the Diffusion of the Swing Riots, 1830–1831

Abstract: Social unrest often begins suddenly and spreads quickly. What is the information that drives its diffusion? How is this information transmitted? And who responds to this information? We present a g...

Using wearable proximity sensors to characterize social contact patterns in a village of rural Malawi

Abstract: Measuring close proximity interactions between individuals can provide key information on social contacts in human communities and related behaviours. This is even more essential in rural settings in low- and middle-income countries where there is a need to understand contact patterns for the implementation of strategies for social protection interventions. We report the quantitative assessment of contact patterns in a village in rural Malawi, based on proximity sensors technology that allows for high-resolution measurements of social contacts. Our results revealed that the community structure of the village was highly correlated with the household membership of the individuals, thus confirming the importance of the family ties within the village. Social contacts within households occurred mainly between adults and children, and adults and adolescents and most of the inter-household social relationships occurred among adults and among adolescents. At the individual level, age and gender social assortment were observed in the inter-household network, and age disassortativity was instead observed in intra-household networks. Moreover, we obtained a clear trend of the daily contact activity of the village. Family members congregated in the early morning, during lunch time and dinner time. In contrast, inter-household contact activity displayed a growth from the morning, reaching a maximum in the afternoon. The proximity sensors technology used in this study provided high resolution temporal data characterized by timescales comparable with those intrinsic to social dynamics and it thus allowed to have access to the level of information needed to understand the social context of the village.

Co-Orientation of Media Use: Studying Selection and Influence Processes in Social Networks to Link Micro Behavior of TV and YouTube Use to Meso-Level Structures

Abstract: Social interactions regarding media content are omnipresent and highlight that media use is closely linked to social life. However, surprisingly little is known about the related social dynamics and their consequences for media use and social relations. This study addresses this topic based on co-orientation theory and investigates the social dynamics of TV and YouTube use among adolescents. A three-wave panel survey among 336 pupils enables us to disentangle which effect the friendship network has on individual media use (RQ1) and which effect media use has on the development and maintenance of friendship ties (RQ2). Based on a multi-level approach of dynamic social network analysis and applying stochastic actor-oriented modeling, we find empirical evidence for processes of social influence regarding TV programs and YouTube channels. No support is found for the hypothesized social selection processes. Along with these empirical insights, the research design demonstrates how the micro-level of individual behavior can be linked with the meso-level of social groups. Furthermore, the insights can be used as a basis to understand larger-scale phenomena emerging on the macro-level of societies and media markets such as audience fragmentation and long-tail audience distributions across media contents.

Toward a New Urban Cycle? A Closer Look to Sprawl, Demographic Transitions and the Environment in Europe

Abstract: Urban growth is a largely debated issue in social science. Specific forms of metropolitan expansion—including sprawl—involve multiple and fascinating research dimensions, making mixed (quali-quantitative) analysis of this phenomenon particularly complex and challenging at the same time. Urban sprawl has attracting the attention of multidisciplinary studies defining nature, dynamics, and consequences that dispersed low-density settlements are having on biophysical and socioeconomic contexts worldwide. The present commentary provides a brief overview on nature and implications of the latent relationship between sprawl, demographic dynamics, and background socio-environmental contexts with special focus on Europe. Empirical evidence supports the idea that spatial planning should cope more effectively with the increasing environmental and socioeconomic exposure of European regions to sprawl and demographic transitions, being progressively far away from a traditional urban cycle with sequential waves of urbanization, suburbanization, counter-urbanization, and re-urbanization. Growing socio-ecological vulnerability of metropolitan regions was evaluated based on a literature review demonstrating how a better comprehension of the intimate linkage between long-term demographic dynamics and urban cycles is necessary to inform fine-tuned policies controlling sprawl and promoting a sustainable management of peri-urban land.

Social dynamics of community resilience building in the face of climate change: the case of three Scottish communities

Abstract: Meeting global targets that maintain temperatures at 1.5 °C above pre-industrial levels while adapting to the growing impacts of climate change requires significant and rapid societal change. Within this context, there has been growing interest in building community resilience to shocks and stressors and as a forward-looking process. Yet while there has been extensive attention to conceptual aspects, there has been much less on how this can be achieved in practice. This research worked with three communities in Scotland (UK) regularly exposed to flooding and other integrated challenges to learn from action about community resilience building. A carefully developed four-tiered transdisciplinary approach was applied that included: relationship-building; enhancing capacities to work with interconnections; enabling processes; and supportive action-oriented research. The findings of the analysis of the system dynamics that were occurring during the resilience-building process highlight that it is a complex and messy social process. Yet, it also shows that if quality and sufficient quantity of support and time to help surface and deliberate on underlying assumptions about communities and change is provided, it can be possible to stimulate emergence of beneficial reinforcing social dynamics that begin to support collaborative and systemic action. To further advance know how about resilience building, much greater focus will be needed on the ‘how’ of resilience. This, in turn, will require new framings of, and approaches for, community resilience and new framings of research, knowledge and knowing.

Bridging sustainability and policing to balinese ormas conflict: an integrative conceptual framework

Abstract: The link between sustainability and policing has not been widely discussed and systematically analyzed in conflict resolution to gain long term goals of post-conflict recovery and reconciliation A fairly large cross-disciplinary literature has developed and proposed a multi-dimensional notion of sustainability in organizational performance including public services and law-enforcement activities Thus, the purpose of this paper is to present a conceptual framework to bridge sustainability practices and policing activities in the background of Balinese mass organization conflict A conceptual literature review is adopted to customize diverse connections of sustainability, policing, and hence conflict The results of the research show that the policing activities may place a stronger focus on conflict resolution by developing sustainable conflict transformation when there are regular conflict potential and a dynamic changing environment The primary conclusion of this paper is that the relationships between sustainability practices and policing activities rely on divergent factors, including social dynamics, culture, organizational structure, and institutional landscapes

Children’s Sociability in Institutional Contexts: Theoretical Reflections on Cognitive Development Within Peer Interactions

Abstract: Human beings are constituted through the presence and actions of others whom they encounter during the course of their lives. We are constituted by all the interactions we enact in different social contexts and through all the meanings we create together about the experiences we share. Therefore, in order to understand the ontogenesis of cognition, one must understand how meanings are constructed with the others we encounter. A substantial amount of research has addressed how infants and toddlers—when in interaction with adults—are able to understand others’ actions and engage in social dynamics by coordinating and regulating adults’ actions. This knowledge has advanced the field of developmental psychology significantly. However, not many efforts have been made to understand the origins of social cognition via peer interactions or explore how peer interactions constitute cognitive development. In this theoretical article, we use the microanalysis of three peer interaction episodes to discuss how the constitutive role of peer experiences can be analysed beyond isolated individual processes. The encounter, the situation and the social and relational process are used as a unit of analysis. This analytical approach considers the contributions and insights provided by the enactive theory, which offers a perspective to understand the processes of cognitive development in interactive experiences.

The role of social structure and dynamics in the maintenance of endemic disease.

Abstract: Social interactions are required for the direct transmission of infectious diseases. Consequently, the social network structure of populations plays a key role in shaping infectious disease dynamics. A huge research effort has examined how specific social network structures make populations more (or less) vulnerable to damaging epidemics. However, it can be just as important to understand how social networks can contribute to endemic disease dynamics, in which pathogens are maintained at stable levels for prolonged periods of time. Hosts that can maintain endemic disease may serve as keystone hosts for multi-host pathogens within an ecological community, and also have greater potential to act as key wildlife reservoirs of agricultural and zoonotic diseases. Here, we examine combinations of social and demographic processes that can foster endemic disease in hosts. We synthesise theoretical and empirical work to demonstrate the importance of both social structure and social dynamics in maintaining endemic disease. We also highlight the importance of distinguishing between the local and global persistence of infection and reveal how different social processes drive variation in the scale at which infectious diseases appear endemic. Our synthesis provides a framework by which to understand how sociality contributes to the long-term maintenance of infectious disease in wildlife hosts and provides a set of tools to unpick the social and demographic mechanisms involved in any given host–pathogen system.

Musical communities in the society of captives: Exploring the impact of music making on the social world of prison:

Abstract: This article examines the ways in which music making can inspire and facilitate social change amongst the “society of captives.” It explores the social dynamics of prison music projects, and then l...

Physical Learning Environment Challenges in the Digital Divide: How to Design Effective Instruction during COVID-19?

Abstract: The coronavirus disease of 2019 (COVID-19) pandemic has changed the way we work, learn, and interact with others in society Academic institutions have responded to the pandemic by shifting face-to-face teaching to online instruction However, whether online instruction succeeds also depends on students’ social and physical learning environment, particularly in developing countries In this paper, we discuss how learning space challenges exacerbate the digital divide We argue that weak digital infrastructure, combined with family and social dynamics, create learning space inequality that negatively influence learning outcomes We provide recommendations on how academic institutions can reimagine content delivery, evaluation, and student support to mitigate learning space inequalities