VII. Our Earthuman Moment: A Major Evolutionary Transition in Individuality
2. Complex Local to Global Network Biosocieties
Gintis, Herbert. Strong Reciprocity and Human Sociality. Journal of Theoretical Biology. 206/2, 2000. Empirical studies can quantify a pervasive tendency for mutual aid among social assemblies.
Gligor, Mircea and Margareta Ignat. Some Demographic Crashes Seen as Phase Transitions. Physica A. 301/535, 2001. Population dynamics exhibit an underlying mathematical basis when modeled by nonlinear statistical theories.
The interest in searching for power laws in the description of complex, collective phenomena is caused by the fact that these power laws are universal, that is to a large degree independent of the microscopic details of the phenomenon. As such, they are typical features of a collective mechanism like the phase transitions: many observables behave as universal power laws in the vicinity of the transition point. Also, the interest for power laws is related to an important property of power laws, namely scale invariance: the characteristic length scale of a physical system at its crritical point is infinite, leading to self-similar, scale-free flucations. (536)
Goldstone, Robert and Marco Janssen. Computational Models of Collective Behavior. Trends in Cognitive Sciences. 9/9, 2005. A survey of how complex systems theory is bringing a new explanatory basis to the human sciences – sociology, economics, psychology, anthropology. By computational is meant the use of “agent-based models” whereby tacit rules inform interactions between autonomous entities as they self-organize into emergent group behaviors.
Goldstone, Robert, et al. Emergent Processes in Group Behavior. Current Directions in Psychological Science. 17/1, 2008. Researchers at Indiana University use agent-based computational models to quantify how human communities of many kinds might take on a life and cognitive capacity of their own.
Just as neurons interconnect in networks that create structured thoughts beyond the ken of any individual neuron, so people spontaneously organize themselves into groups to create emergent organizations that no individual may intend, comprehend, or even perceive. (10) Social phenomena such as the spread of gossip, the World-Wide Web, the popularity of cultural icons, legal systems, and scientific establishments all take on a life of their owe, complete with their own self-organized divisions of labor and specialization, feedback loops, growth, and adaptations. (10)
Guimera, R., et al. Self-Similar Community Structure in a Network of Human interactions. Physical Review E. 065103, 2003. In theory complex networks form a hierarchical structure of nested “communities.” This is borne out by a study of a large university email system. The authors go on to state that such “spontaneous self-organization” is an example of a universally present natural principle.
By using the same argument, one can expect that the scaling behavior we obtain should be observable in any human social network. At the same time, the similarity with river networks suggests that a common principle of optimization – of flow of information in organizations or of flow of water in rivers – could be the underlying driving force in the formation and evolution of social networks. (065103-4)
Hackenberg, Robert and Beverly Hackenberg. Notes Toward a New Future: Applied Anthropology in Century XXI. Human Organization. 63/4, 2004. Still another field, in this case to also be “postmodern,” finds that “nonlinear dynamic systems” theories are especially suitable to advance the study of multifaceted human societies. The main paper is An Anthropological Problem, A Complex Solution by Michael Agar whence “a narrative of connections and contingencies” and agent-based modeling can apply, e.g., to urban epidemics of illicit drug use.
Hall, Gavin and William Bialek. The Statistical Mechanics of Twitter. arXiv:1812.07029. As a global science proceeds on its electronic own, cross-informative networks are forming between widely separate fields. Here is an exemplary paper by Princeton University theorists which reports a connection in kind between webwide social chatter and physical dynamics. It is noted that this public verbose media tends to critical attractor modes. Once more across a broad stretch from uniVerse to usVerse, a common, recurrent, biterate conservation and discourse goes on. See also Searching for Collective Behavior in a Small Brain by W. Bialek and colleagues (1810.07623).
We build models for the distribution of social states in Twitter communities which can be defined by the participation vs. silence of individuals in conversations that surround key words. We approximate the joint distribution of these binary variables using the maximum entropy principle, finding the least structured models that match the mean probability of individuals tweeting and their pairwise correlations. These models provide accurate, quantitative descriptions of higher order structure in these social networks. The parameters of these models seem poised close to critical surfaces in the space of possible models, and we observe scaling behavior of the data under coarse-graining. These results suggest that simple models, grounded in statistical physics, may provide a useful point of view on the larger data sets now emerging from complex social systems. (Abstract)
Hamilton, Marcus, et al.
Nonlinear Scaling of Space Use in Human Hunter-Gatherers.
Proceedings of the National Academy of Sciences.
This report grew from research programs of James Brown’s group at the University of New Mexico, which studies biocomplexity, scaling and macroecology. It merits special notice because this work is one of the first quantifications of how human groupings take on the same patterns and processes as an organism. What can then be broadly implied is a nested biological continuity throughout emergent evolution, of which, as long proposed, human social community can be appreciated with isomorphic kinship to a somatic and cerebral organic entity.
The result is a complex social structure in which resources flow through social networks, which exhibit self-similar or fractal-like hierarchical scaling and are strikingly similar, quantitatively, to the hierarchically branched vascular networks that distribute metabolic resources within the bodies of plants and mammals and water from river drainage basins. (4765) Our results demonstrate that individual space use in hunter-gatherer societies scales nonlinearly or allometrically with population size. Furthermore, this power-law scaling relation is robust to differences in trophic foraging niche, ecosystem temperature, energy availability, geographic location, and cultural phylogeny. (4768)
Hamilton, Marcus, et al.
The Complex Structure of Hunter-Gather Social Networks.
Proceedings of the Royal Society B.
Researchers from the Universities of New Mexico and Chicago, and Santa Fe Institute, report that after many years of nonlinear studies, living systems from cells to cities can be known to spring from and be distinguished by the self-organizing dynamics of interactive entities. These propensities then proceed to create a nested, iterative societal scale. As the authors cite, this same phenomena occurs everywhere from physical and chemical phases to continental civilizations.
In nature, many different types of complex system form hierarchical, self-similar or fractal-like structures that have evolved to maximize internal efficiency. In this paper, we ask whether hunter-gatherer societies show similar structural properties. We use fractal network theory to analyze the statistical structure of 1189 social groups in 339 hunter-gatherer societies from a published compilation of ethnographies. We show that population structure is indeed self-similar or fractal-like… this remarkable self-similarity holds both within and across cultures and continents. We show that the branching ratio is related to density-dependent reproduction in complex environments and hypothesize that the general pattern of hierarchical organization reflects the self-similar properties of the networks and the underlying cohesive and disruptive forces that govern the flow of material resources, genes and non-genetic information within and between social groups. Our results offer insight into the energetics of human sociality and suggest that human social networks self-organize in response to similar optimization principles found behind the formation of many complex systems in nature. (2195)
Hamilton, Marcus, et al. The Ecological and Evolutionary Energetics of Hunter-Gather Residential Mobility. Evolutionary Anthropology. 25/3, 2016. . In an issue on Evolution of Human Mobility, a southwest, Santa Fe Institute, team of MH, Jose Lobo, Eric Ripley, Hyejin Youn, and Geoffrey West proceed to reconstruct this early phase by way of these qualitative aspects. See also by this group Nonlinear Scaling of Space Use in Human Hunter-Gatherers (PNAS 104/4765, 2007) and The Complex Structure of Hunter-Gatherer Social Networks (Proceedings of the Royal Society B 274/2195, 2007). And we wonder Whom is worldwise Anthropo/Cosmo Sapiens to retrospectively do this, what does it mean to realize that our daily, communal lives are moved and constrained by a mathematical independence?
Residential mobility is a key aspect of hunter-gatherer foraging economies and therefore is an issue of central importance in hunter-gatherer studies. Hunter-gatherers vary widely in annual rates of residential mobility. Understanding the sources of this variation has long been of interest to anthropologists and archeologists. The vast majority of hunter-gatherers who are dependent on terrestrial plants and animals move camp multiple times a year because local foraging patches become depleted and food, material, and social resources are heterogeneously distributed through time and space. In some environments, particularly along coasts, where resources are abundant and predictable, hunter-gatherers often become effectively sedentary. But even in these special cases, a central question is how these societies have maintained viable foraging economies while reducing residential mobility to near zero. (Abstract)
Hammerstein, Peter and Edward Hagen. The Second Wave of Evolutionary Economics in Biology. Trends in Ecology and Evolution. 20/11, 2005. In the 1970’s and 1980’s, biologists and economists borrowed concepts from each other such as optimal foraging theory, game theory, and analogies between adaptation by natural selection and rational decision making. But the two disciplines had little interaction. Recently a new phase of joint exploration has commenced which this article documents. One result is an appreciation of “a desire for prosocial outcomes that value the welfare of others.”
Hanson, F. Allan. The New Superorganic. Current Anthropology. 45/4, 2004. Prior concepts of “methodological individualism” or the old “superorganic” as a collective group are updated in terms of an “extended agency.” This revised view which draws on artificial intelligence to characterize human assemblies as fluid, variable, information processing activities, akin to neural networks.