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VII. Our Earthuman Ascent: A Major Evolutionary Transition in Twndividuality2. Complex Local to Global Network Biosocieties Yang, Zhaohui and Kshitji Jerath. Multi-scale Traffic Flow Modeling: A Renormalization Group Approach. arXiv: 2403.13779. UMass Lowell engineers achieve a unique advancement in the mathematical study of human mobilities from the viewpoint of a significant physical phenomena, as the title notes. At once the work identifies this double dimension and serves to trace and connect our Earthuman travels with universal principles.
Youngman, Paul and Mirsad Hadzikadic, eds. Complexity and the Human Experience: Modeling Complexity in the Humanities and Social Sciences. Singapore: Pan Stanford Publishing, 2014. An initial volume which gathers much material that can illustrate how complex system revisions have spread to and reinvigorated every field and aspect. Thus another application of generic “complex adaptive systems” in this cultural realm is achieved. Typical chapters are Complexity Theory and Political Change: Talcott Parsons Occupies Wall Street by Martin Zwick, and Scientific Paradigms in US Policy: Is It Time for Complexity Science? By Michael Givel and Liz Johnson. Complexity science is the study of how large numbers of relatively simple entities organize themselves into a collective whole that creates patterns, uses information, and, in some cases, evolves and learns. Those collective wholes that do not evolve and learn are complex systems; those that do are complex adaptive systems (CAS). Complexity and its various systems have been a topic of study in the natural sciences for decades already Physics, chemistry, biology, mathematics, meteorology, and engineering practitioners have used the concept of complex systems to explain phenomena as diverse as phase transitions in physical matter, immune system functions, and weather patterns. Our authors show how complexity ontology with its corresponding emphasis on modeling has already effectively spread to the social sciences and is at the very threshold of making a significant impact on the humanities has already effectively spread to the social sciences and is at the very threshold of making a significant impact on the humanities. (Introduction Abstract) Zhou, Wei-Zing, et al. Discrete Hierarchical Organization of Social Group Sizes. Proceedings of the Royal Society B. 272/439, 2005. An international team of social theorists that includes Zhou, East China University of Science and Technology, Didier Sornette, UCLA and Universite´de Nice-Sophia Antipolis, Russell Hall, University of Durham, and Robin Dunbar, University of Liverpool, find a fascinating mathematical pattern and sequence to underlie and guide human sociability. As the quote conveys, a primate and hominid evolutionary past continues on to our propensity to aggregate into nested, sequentially larger, assemblies. Their iterative formation is further noticed to follow a fractal self-similarity, nature’s repetitive creativity arises apace. But these quantitative insights, if availed, may then reveal and teach a better way forward. Rather than each child as a lone learner, children might prosper more in small, mixed, supportive teams. Moving up the scale, as Sustainable Ecovillages reports, a nominal 100 folks, the archetypal tribe, band, or clan size, again serves these intentional, reciprocal communities. The ‘social brain hypothesis’ for the evolution of large brains in primates has led to evidence for the coevolution of neocortical size and social group sizes, suggesting that there is a cognitive constraint on group size that depends, in some way, on the volume of neural material available for processing and synthesizing information on social relationships. More recently, work on both human and non-human primates has suggested that social groups are often hierarchically structured. We combine data on human grouping patterns in a comprehensive and systematic study. Using fractal analysis, we identify, with high statistical confidence, a discrete hierarchy of group sizes with a preferred scaling ratio close to three: rather than a single or a continuous spectrum of group sizes, humans spontaneously form groups of preferred sizes organized in a geometrical series approximating 3–5, 9–15, 30–45, etc. Such discrete scale invariance could be related to that identified in signatures of herding behaviour in financial markets and might reflect a hierarchical processing of social nearness by human brains. (Abstract, 439) Zingg, Christian, et al. What is the Entropy of a Social Organization? Entropy. 21/9, 2019. ETH Zurich, System Design researchers including Frank Schweitzer achieve a novel network characterization of behavioral activities by overtly viewing members as node points which are then linked by constant, informational interconnections. By this constructive application, still another archetypal manifestation of nature’s quantome to genome, neurome, and textome universality continues forth to grace our busy groupings. We quantify a social organization’s potentiality to attain different network configurations in which nodes correspond to individuals and edges to their multiple interactions. Altogether these models are treated as a network ensemble. To have the ability to encode interaction preferences, we choose the generalized hypergeometric form of random graphs, as described by a closed-form probability distribution. From this distribution we calculate Shannon entropy as a measure of potentiality. This allows us to compare different organizations as well as different stages in their development. The feasibility of the approach is demonstrated using data from three empirical and two synthetic systems. (Abstract edits)
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