VII. Our Earthuman Ascent: A Major Evolutionary Transition in Twindividuality

3. Planetary Physiosphere: Anatomics, Economics, Urbanomics

Bettencourt, Luis, et al. The Self-Similarity of Human Social Organization and Dynamics in Cities. Lane, David, et al, eds. Complexity Perspectives in Innovation and Social Change. Berlin: Springer, 2009. With co-authors Jose Lobo and Geoffrey West, an effort to quantify how cities really might be analogously akin to biological organisms. In so doing, a universality of hierarchical network patterns and information processes are found to grace urban settlements of all kinds no matter where on earth or in history. One wonders if a term such as “urbanism” might be an apt for this viable organic social abidance. See also “The Organization of Urban Systems” by Anne Bretagnolle, et al, in the same volume.

We have shown that power law scaling is a pervasive property of human social organization and dynamics in cities and holds across time and for different nations with very different levels of development, economic sector distribution, and with different cultural norms and geographic location. This is an extraordinary assertion indicating that, on average, different cities are scaled up versions of each other, particularly in terms of rhythms of social activity – such as the creation of wealth and ideas, infectious contacts and crime, and patterns of human behavior. (234)

Bettencourt, Luis, et al. Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities. PLoS One. 5/11, 2010. With co-authors Jose Lobo, Santa Fe Institute, Deborah Strumsky, University of North Carolina, and Geoffrey West, LANL, an extensive quantification is achieved of a nested invariance from neighborhoods to metropolis. Several prime parameters as noted that appear to hold independently of city or nation are described with a validity not possible earlier. But philosophical reflection is in order as one more example of an implicate, mathematical source that manifestly structures and guides our personal and communal lives, that we are just becoming aware of, and can intentionally avail for a more humane abide.

In this paper, we have proposed a systematic procedure for solving the long-standing problem of constructing meaningful, science-based metrics for ranking and assessing local features of cities. By using nonlinear urban scaling laws as a baseline, our procedure accounts for the underlying principles and socioeconomic dynamics that give rise to cities to distinguish general effects of urbanism from local dynamics and, consequently, leads to a much simpler and direct perspective into the local factors that make or break specific places. (6) The general regularity of urban scaling laws and of the statistics of their deviations point to the possibility of a general theory of cities that can account for the essence of these interactions and predict a small set of fundamental scaling regularities common to all urban systems. (6)

From this viewpoint, the general statistically stable properties of cities emerge as a hierarchy of interrelated fundamental quantities. (7) Analogously, we have shown that scaling laws for socioeconomic and infrastructural metrics persist over time and across every nation that has been studied, and that these organize urban quantities into two broad universality classes of dynamics that manifest either increasing returns to scale (socioeconomic quantities) or economies of scale (material infrastructure) both to approximately the same degree. (7) It is therefore extraordinary that, despite the immense diversity of human and social behavior, the dynamics and organization of urban systems, as well as of individual cities, is an emergent predictable phenomenon. (7)

Bouchard, Jean-Philippe. The Self-Organized Criticality Paradigm in Economics & Finance. arXiv:2407.10284. We came to this entry from Markus Aschwanden’s Power Laws Associated with Self-Organized Criticality paper (2505.00748) wherein his astronomic SOC findings can be seen to extend in kind from coronae to metabolisms to informatics. Herein a senior European theorist describes how this optimum natural phenomenon appears equally evident in hyperactive monetary commerce. See also Critical fragility socio-technical systems by Jose Moran, et al at arXiv:2307.03546 for another J-P B paper.

Self-Organized Criticality (SOC) is the mechanism by which complex systems spontaneously settle close to a critical edge between stability and chaos. In this short review, we discuss how SOC could offer a plausible solution to the excess volatility puzzle in financial markets. We argue that in general the quest for efficiency and the necessity of *resilience* may be mutually incompatible and thus require specific policy considerations.

Jean-Philippe Bouchaud is a French physicist, co-founder chairman of Capital Fund Management, adjunct professor at École Normale Supérieure and held the Bettencourt Innovation Chair at Collège de France in 2020.

Bramoulle, Yann, et al, eds. The Oxford Handbook of the Economics of Networks. New York: Oxford University Press, 2016. Whence this conceptual advance is found to explain human social commerce, where connects individual (nodal) behavior through informed interrelations. As this nonlinear revolution is becomes similarly applied from cosmic clusters to human business, it is worth noting that while particulate objects or entities are readily visible, equally real linkages are not apparent, and missed until now. See also, for example Revealing the Hidden Structure of Dynamic Ecological Networks, search Mathias.

The Oxford Handbook of the Economics of Networks represents the frontier of research into how and why networks they form, how they influence behavior, how they help govern outcomes in an interactive world, and how they shape collective decision making, opinion formation, and diffusion dynamics. Theoretical work in network formation, games played on networks, repeated games, and the interaction between linking and behavior is synthesized. A number of chapters are devoted to studying social process mediated by networks (such as) opinion formation, diffusion of information and disease, and learning. Another section discusses communities, with applications including social trust, favor exchange, and social collateral; the importance of communities for migration patterns; and the role that networks and communities play in the labor market. (Publisher excerpts)

Bronk, Richard. The Romantic Economist. Cambridge: Cambridge University Press, 2009. As is well known, there is something deeply amiss about our finances and markets. In this unique work the author combines an academic base at the London School of Economics with years as a fund manager for the Bank of England to critique a vested mechanical system that is quite breaking down. A scholarly historical vista can reveal an alternative Romantic way, with commerce conceived as rightly organic in kind. As a result, these two modes, reading much as right feminine and left masculine brain attributes, might join in salutary synthesis if further conceived as dynamically self-organized complex adaptive systems.

Burghardt, Keith, et al. Universal Patterns in the Long-term Growth of Urban Infrastructure in U.S. Cities from 1900 to 2015. arXiv:2412.13181. While areas are often felt to be chaotic, USC, Information Sciences Institute and University of Colorado, Institute of Behavioral Science analysts including Stefan Leyk report finding the presence of consistent, similar, nested levelings across disparate spatial and temporal, small and large occasions. Their datasets also include many societal features as the Abstract notes. Once again a deeper, implicate, domain is shown to guide its regular explicate formations, as epidemic studies have found. This geno/phenotype-like arrangement will be a prime realization going forward.

Despite the rapid growth of cities, our understanding of they grow remains limited. Thus, the scaling laws between a city's features and its population as they evolve over time is under-explored. In this paper, we leverage novel data sources and analyze the temporal scaling laws of developed area, building indoor area, building footprint area, and road statistics for metropolitan areas for 115 years. Three notable patterns emerge. First, scaling law exponents imply many urban areas are becoming less dense and indoor area per capita increases as cities grow. Second, larger cities tend to have a smaller scaling exponent than smaller cities. Third, growth patterns are similar between nearby cities. These results help urban planners and scientists understand universal, long-term patterns of city growth across the US. (Excerpt)

Bury, Thomas. A Statistical Physics Perspective on Criticality in Financial Markets. Journal of Statistical Mechanics. Online November, 2013. Apropos, the paper by a Universite Libre de Bruxelles econophysicist starts off as almost every contribution of this kind by noting in the opening paragraph how certain dynamic phenomena to be discussed is the same as being found everywhere else across nature and society. This contrast is significant here because of its scope from physical realms to global complexities. While researchers rarely go the next step, all these findings beg an independent, universal activity of a programmatic source that impels and manifests, as if a genetic code, at each and every phase and instance. For another interdisciplinary view see “Ecosystems Perspective on Financial Networks” by Eduardo Viegas, et al in Complexity (19/1, 2013).

Stock markets are complex systems exhibiting collective phenomena and particular features such as synchronization, fluctuations distributed as power-laws, non-random structures and similarity to neural networks. Such specific properties suggest that markets operate at a very special point. Financial markets are believed to be critical by analogy to physical systems but few statistically founded evidence have been given. Through a data-based methodology and comparison to simulations inspired by statistical physics of complex systems, we show that the Dow Jones and indices sets are not rigorously critical. However, financial systems are closer to the criticality in the crash neighborhood. (Abstracts)

Moreover, financial systems are closer to the criticality close to the crash beginning meaning large fluctuation and large deviation from the uniform distribution of the configurations. This evolution also suggests a process of self-organization. The market is a highly adaptive system. By self-organization, the market reacts strongly to a change, unexpected events and by itself does not consider all possible events as equiprobable. However through the data analysis, the stock exchanges system is not exactly critical and the Dow Jones seems to be far from criticality. Furthermore, financial systems do not stay in the same regime and get closer to the criticality just before a crisis. An interesting finding since in such models, large avalanches occur more likely close to the criticality. (Conclusion)

Bustos, Sebastian, et al. The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems. PLoS One. 7/11, 2012. We note this work because Bustos with Charles Gomez, Ricardo Hausmann and Cesar Hidalgo, Harvard, MIT, and Stanford management scientists, make especial notice of this propensity for repetitive wholes within wholes, as everywhere else, even in such a commercial-technical extent.

In economic systems, the mix of products that countries make or export has been shown to be a strong leading indicator of economic growth. Hence, methods to characterize and predict the structure of the network connecting countries to the products that they export are relevant for understanding the dynamics of economic development. Here we study the presence and absence of industries in international and domestic economies and show that these networks are significantly nested. This makes the appearance and disappearance of individual industries in each location predictable. We show that the model can reproduce the high level of nestedness observed in these networks only when we assume a high level of heterogeneity in the distribution of capabilities available in countries and required by products. In the context of the neutral model, this implies that the high level of nestedness observed in these economic networks emerges as a combination of both the complementarity of inputs and heterogeneity in the number of capabilities available in countries and required by products. (Abstract)

Carbone, Anna, et al. Atlas of Urban Scaling Laws. Journal of Physics: Complexity. June, 2022. Four Polytechnical University of Torino physicists provide a substantial proof to date that nature’s nested self-similar patternings which are now found to grace every other instance likewise play a formative role even for large metropolitan cities. One might note that a current ability to use sophisticated aerial images could be seen as a present whole Earthropocene learning process so as to quantify, vivify, and make better.

Accurate estimates of an urban fractal dimension are obtained by way of a detrended moving average algorithm on high-resolution multi-spectral satellite images from the WorldView2 (WV2) database covering the major European cities. Highly sensitive and repeatable satellite records yield robust local estimates of the urban scaling exponents. Our work discusses how to discriminate among different scaling theories on the way to a more formal adoption of the complex system science methods to urban landscape analysis and planning. (Abstract excerpt)

Chen, Ting-Ting, et al. New Approaches in Agent-Based Modeling of Complex Financial Systems. Frontiers of Physics. 12/6, 2017. We cite this entry in an online Springer journal by Zhejiang University, China systems theorists as an example among many of how economic markets similarly appear to exemplify and be driven by the same universal mathematics as everywhere else. The issue is a Soft-Matter Physics and Complex Systems collection.

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents’ behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems. (Abstract)

Chen, Uanguang and Bin Jiang. Hierarchal Scaling in Systems of Natural Cities. arXiv:1608.05770. We cite this posting to enter a series of papers by the Peking University and University of Gavle, Sweden systems geographers, with colleagues, which quantify how nature’s universal complex patterns and dynamics are quite manifest in human settlements from hamlets to a metropolis. See also Modeling Fractal Dimension Curve of Urban Growth in Developing Countries (1608.02053), A Topological Representation for Taking Cities as a Coherent Whole (1607.07169), A Complex Network Perspective on (Christopher) Alexander’s Wholeness (1602.08939), and A Fractal Perspective on Scale in Geography (1509.08419).

Hierarchies can be modeled by a set of exponential functions, from which we can derive a set of power laws indicative of scaling. These scaling laws are followed by many natural and social phenomena such as cities, earthquakes, and rivers. This paper is devoted to revealing the scaling patterns in systems of natural cities by reconstructing the hierarchy with cascade structure. The cities of America, Britain, France, and Germany are taken as examples to make empirical analyses. The hierarchical scaling relations can be well fitted to the data points within the scaling ranges of the size and area of the natural cities. The size-number and area-number scaling exponents are close to 1, and the allometric scaling exponent is slightly less than 1. The results suggest that natural cities follow hierarchical scaling laws and hierarchical conservation law. Zipf's law proved to be one of the indications of the hierarchical scaling, and the primate law of city-size distribution represents a local pattern and can be merged into the hierarchical structure based on big datasets. (Abstract)

Chen, Yanguang and Yixing Zhou. Multi-Fractal Measures of City-Size Distributions Based on the Three-Parameter Zipf Model. Chaos, Solitons and Fractals. 22/4, 2004. Another contribution from the Peking University Department of Geography on the formation and viability of human settlements.

Fractal city systems is a pioneering study of the development and use of fractal geometry for understanding and planning the physical form and spatial network of cities. (793) Fractal hierarchies of cities conform to the law of the unity of opposites on the relationships between micro- and macro-state, disorder and order, randomness and determination, simplicity and complexity, and so forth. (802)

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