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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VII. Our Earthuman Ascent: A Major Evolutionary Transition in Twndividuality

2. Complex Local to Global Network Biosocieties

Levinson, Stephen and Pierre Jaisson. Evolution and Culture. Cambridge: MIT Press, 2005. Out in November, the proceedings of a Fyssen Foundation symposium on behavioral, functional, linguistic, and especially cognitive adaptations for cultural human society.

Li, Angsheng and Pan Peng. Community Structures in Classical Network Models. Internet Mathematics. 7/2, 2011. After a decade of worldwide studies of these evident natural and cultural propensities, once known as Indra’s Web, Chinese Academy of Sciences computation specialists can go on to theoretically explain this constant tendency of vital systems to form or cluster into viable modular assemblies. By so doing, a further measure of robustness is imparted to the universal nested network interconnectedness and interdependency of a genesis cosmos. And by intentional avail, could such indigenous wisdom suggest a more viable future of social ecovillage “protocells?” Professor Li is also cochair of the 2012 Turing Centenary Conference in China. See also “The Small-Community Phenomenon in Networks” by the authors posted July 2011 at arXiv:1107.5786.

Communities (or clusters) are ubiquitous in real-world networks. Researchers from different fields have proposed many definitions of communities, which are usually thought of as a subset of nodes whose vertices are well connected with other vertices in the set and have relatively fewer connections with vertices outside the set. In contrast to traditional research that focuses mainly on detecting and/or testing such clusters, we propose a new definition of community and a novel way to study community structure, with which we are able to investigate mathematical network models to test whether they exhibit the small-community phenomenon, i.e., whether every vertex in the network belongs to some small community. (Abstract, 81)

Communities are naturally thought of as cohesive subgraphs in a network. Informally, vertices in a community are well interconnected with fellow members of the community and have relatively fewer connections with vertices outside the community. Communities appear in a wide range of applications. For instance, in protein-protein interaction networks, groups of proteins sharing the same or similar functions are clustered together, in society, the communities may correspond to groups of friends or coworkers, in scientific collaboration networks, scientists who investigate similar research topics or use similar methodologies group together to form communities. (82)

Given that networks are natural mathematical models for describing relationships of massive objects in many different subjects of both the physical and social sciences, it is an important scientific problem to study the functions, roles, and mechanisms of small communities of general networks in nature, in industry, and in society. In this article, we have proposed a novel approach to defining communities in a network, allowing us to study the small-community phenomenon in some well-defined network models. We show that a number of natural network models satisfy the small-community phenomenon, which can be regarded as a new feature for a number of networks. (102-103)

Macy, Michael, and Robert Willer. From Factors to Actors: Computational Sociology and Agent-Based Modeling. Annual Review of Sociology. Vol. 28, 2002. Social scientists are lately coming to universal nonlinear systems science as a way to understand their immensely subject. This cogent introduction again defines many autonomous entities which through their interdependent relations, according to simple rules, self-organize an emergent pattern and behavior.

Sociologists often model social processes as interactions among variables. We review an alternative approach that models social life as interactions among adaptive agents who influence one another in response to the influence they receive. (143)

Manrique, Pedro, et al. Shockwaves and Turbulence across Social Media. arXiv:2210.14382. George Washington University sociophysicists including Neil Johnson continue their project to show how all manner of wild public phenomena from terrorism, hot conflicts, epidemics to online rants in this case can yet be seen to hold to and exhibit complex system dynamics. Once ever again, since one same genetic-like source code programs this organic ecosmos, its formative presence is in effect everywhere.

Online communities featuring 'anti-X' hate and extremism, somehow thrive online despite moderator pressure. We present a first-principles theory of their dynamics, which accounts for the fact that the online population comprises diverse individuals and evolves in time. The resulting equation represents a novel generalization of nonlinear fluid physics and explains the observed behavior across scales. Its shockwave-like solutions explain how, why and when such activity rises from 'out-of-nowhere', and show how it can be delayed, re-shaped and even prevented by adjusting the online collective chemistry. This theory and findings should also be applicable to anti-X activity in next-generation ecosystems featuring blockchain platforms and Metaverses.

Mantovani, M., et al. Scaling Laws and Universality in the Choice of Election Candidates. Europhysics Letters. 96/4, 2011. From the Universidade Estadual de Maringá, Departamento de Física, and National Institute of Science and Technology for Complex Systems, Brazil, still another quantification that each and every realm of reality is distinguished by a duality of manifest, exemplary behavior, and an immaterial, mathematic, ultimately genetic, source it arises from.

Nowadays there is an increasing interest of physicists in finding regularities related to social phenomena. This interest is clearly motivated by applications that a statistical mechanical description of the human behavior may have in our society. By using this framework, we address this work to cover an open question related to elections: the choice of elections candidates. Our analysis reveals that, apart from the social motivations, this system displays features of traditional out-of-equilibrium physical phenomena such as scale-free statistics and universality. Basically, we found a non-linear (power law) mean correspondence between the number of candidates and the size of the electorate, and also that this choice has a multiplicative underlying process (lognormal behavior). The universality of our findings is supported by data from 16 elections from 5 countries. In addition, we show that aspects of network scale-free can be connected to this universal behavior. (Abstract, 48001)

Social phenomena are nowadays ubiquitous in the research performed by many physicists. In these investigations, the human behavior plays a central role and it constitutes the basic ingredient of the emergent picture. However, despite the complex scenario related to human activities, statistical physics models have been successfully applied to explain collective aspects of social systems. This success gives rise to the possibility that, similarly to large-scale physical thermodynamic systems, large groups of interacting humans may exhibit universal statistical properties. For the society organization in general, this statistical mechanical description of the human activities seems to be promising in resource management, service allocation, political strategies, among others. (Introduction, 48001)

Marsalla, Anthony. Toward a ‘Global-Community Psychology.’. American Psychology. 53/12, 1998. An expansion of psychological science beyond its Western phase is recommended to become more multicultural, ethnically correct, and racially sensitive, in order to face the intense personal and social issues of a world society.

Masuda, Takahiko and Richard Nisbett. Culture and Change Blindness. Cognitive Science. 30/2, 2006. When scenic or urban images are shown to participants and then slightly altered, East Asians attend more to contextual settings, while Westerners preferentially focus on individual objects.

Mayntz, Renate. Chaos in Society. Grebogi, C. and James Yorke, eds. The Impact of Chaos on Science and Society. Toyko: United Nations University Press, 1997. A more appropriate sociological science ought to be informed by the dynamics of nonlinear self-organization.

Human societies obviously display all the characteristic features of nonlinear non-equilibrium systems: unpredictability due to complex interdependencies and recursive processes, hysteresis, phase transitions, and critical mass phenomena. (300)

Mesoudi, Alex. Cultural Evolution: How Darwinian Theory can Explain Human Culture and Synthesize the Social Sciences. Chicago: University of Chicago Press, 2011. With this book and prior articles (search here and AM’s website), the University of London psychologist is in the forefront of a 21st century quantitative confirmation, long in the offing, of a seamless continuity (how could it be otherwise) between prior biological and recent societal realms. As noted below, “culture” includes linguistic, psychological, economic, neural, and ethnic dimensions. Compare with Etienne Danchin, et al, with AM as a coauthor, as a new generation of researchers are able to join much recent evidence to flesh out and confirm this expanded evolutionary developmental syntheses. An update article by AM is Cultural Evolution: A Review in Evolutionary Biology (Online April, 2015).

In this book I survey a growing body of scientific research that is based on the fundamental premise that cultural change – by which I mean changes in socially transmitted beliefs, knowledge, technology, languages, social institutions, and so on – shares the very same principles that Darwin applied to biological change in The Origin a century and a half ago. In other words, culture evolves. (viii)

Mesoudi, Alex. How Cultural Evolutionary Theory Can Inform Social Psychology and Vice Versa. Psychological Review. 116/4, 2009. From the University of London, an update on Mesoudi’s project, along with colleagues cited in a long bibliography, to at last forge a realistic, comprehensive parallel and continuity between biological evolution and the currency of human linguistic societies. By such an achievement, it is contented that various academic disciplines which deal with similar aspects can be effectively informed and expanded in their theoretical and practical endeavors.

Cultural evolutionary theory is an interdisciplinary field in which human culture is viewed as a Darwinian process of variation, competition, and inheritance, and the tools, methods, and theories developed by evolutionary biologists to study genetic evolution are adapted to study cultural change. (929)

Mesoudi, Alex. Pursuing Darwin’s Curious Parallel: Prospects for a Science of Cultural Evolution. Proceedings of the National Academy of Sciences. 114/7853, 2017. As the extended Abstract says, the University of Exeter cultural psychologist (search) continues his project, as David S. Wilson and others, to reconcile and join life’s biological phase with our human linguistic societies. A working answer is in sight as better finesses of field, experimental, and conceptual domains come aboard. See also by AM and collaborators Shared Group Membership Facilitates the Persistence of Cultural Transmitted Behavior (PsyArXiv 2018)

In the past decades, scholars have pursued the curious parallel noted by Darwin between the genetic evolution of species and the cultural evolution of beliefs, skills, knowledge, languages, institutions, and socially transmitted information. Here, I review current progress in the pursuit of an evolutionary science of culture that is grounded in both biological and evolutionary theory, but also treats culture as more than a proximate mechanism that is directly controlled by genes. Both genetic and cultural evolution can be described as systems of inherited variation that change over time in response to processes such as selection, migration, and drift. The foundation of cultural evolution was laid in the late 20th century with population-genetic style models of cultural microevolution, and by phylogenetic methods. Since then, there have been major efforts to understand the sociocognitive mechanisms underlying cumulative cultural evolution, the consequences of demography along with social learning biases, transformative and selective processes, and quantitative phylogenetic and multilevel selection models. (Abstract excerpts)

Mesoudi, Alex, et al. Is Human Cultural Evolution Darwinian? Evolution. 58/1, 2004. An update on the contentious project from Charles Darwin to the present to explain a continuity of biological and social evolution. A main issue is identifying the cultural units of inheritance, such as memes, which seems to be a matter of semantic definition.

In short, the unifying framework of Darwinian evolution has the potential to synthesize the social sciences as it has the natural sciences. (9)

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