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      Cities: Complexity, theory and history

      research-article
      1 , 2 , * , 3 , 4
      PLoS ONE
      Public Library of Science

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          Abstract

          In recent decades researchers in a variety of disciplines have developed a new “urban science,” the central goal of which is to build general theory regarding the social processes underlying urbanization. Much work in urban science is animated by the notion that cities are complex systems. What does it mean to make this claim? Here we adopt the view that complex systems entail both variation and structure, and that their properties vary with system size and with respect to where and how they are measured. Given this, a general framework regarding the social processes behind urbanization needs to account for empirical regularities that are common to both contemporary cities and past settlements known through archaeology and history. Only by adopting an explicitly historical perspective can such fundamental structure be revealed. The identification of shared properties in past and present systems has been facilitated by research traditions that define cities (and settlements more broadly) as networks of social interaction embedded in physical space. Settlement Scaling Theory (SST) builds from these insights to generate predictions regarding how measurable properties of cities and settlements are related to their population size. Here, we focus on relationships between population and area across past settlement systems and present-day world cities. We show that both patterns and variations in these measures are explicable in terms of SST, and that the framework identifies baseline infrastructural area as an important system-level property of urban systems that warrants further study. We also show that predictive theory is helpful even in cases where the data do not conform to model predictions.

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          Most cited references63

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            The origins of scaling in cities.

            Despite the increasing importance of cities in human societies, our ability to understand them scientifically and manage them in practice has remained limited. The greatest difficulties to any scientific approach to cities have resulted from their many interdependent facets, as social, economic, infrastructural, and spatial complex systems that exist in similar but changing forms over a huge range of scales. Here, I show how all cities may evolve according to a small set of basic principles that operate locally. A theoretical framework was developed to predict the average social, spatial, and infrastructural properties of cities as a set of scaling relations that apply to all urban systems. Confirmation of these predictions was observed for thousands of cities worldwide, from many urban systems at different levels of development. Measures of urban efficiency, capturing the balance between socioeconomic outputs and infrastructural costs, were shown to be independent of city size and might be a useful means to evaluate urban planning strategies.
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              Economic growth in a cross-section of cities

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 December 2020
                2020
                : 15
                : 12
                : e0243621
                Affiliations
                [1 ] Department of Anthropology, University of Colorado Boulder, Boulder, Colorado, United States of America
                [2 ] Santa Fe Institute, Santa Fe, New Mexico, United States of America
                [3 ] School of Sustainability, Arizona State University, Tempe, Arizona, United States of America
                [4 ] School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America
                University at Buffalo - The State University of New York, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-0709-5287
                Article
                PONE-D-20-28450
                10.1371/journal.pone.0243621
                7723246
                33290411
                ef1a1238-8db7-49cc-bf78-2a105ccc11b9
                © 2020 Ortman et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 September 2020
                : 24 November 2020
                Page count
                Figures: 6, Tables: 3, Pages: 24
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000913, James S. McDonnell Foundation;
                Award ID: 220020438
                Award Recipient :
                Portions of this research were supported by a grant from the James S. McDonnell Foundation (#220020438, to SO): https://www.jsmf.org/. Additional support has been provided by the Arizona State University / Santa Fe Institute Center for Biosocial Complex Systems. There was no additional external funding received for this study.
                Categories
                Research Article
                Earth Sciences
                Geography
                Human Geography
                Urban Geography
                Cities
                Social Sciences
                Human Geography
                Urban Geography
                Cities
                Engineering and Technology
                Civil Engineering
                Urban Infrastructure
                Computer and Information Sciences
                Systems Science
                Complex Systems
                Physical Sciences
                Mathematics
                Systems Science
                Complex Systems
                Earth Sciences
                Geography
                Human Geography
                Urban Geography
                Urban Areas
                Social Sciences
                Human Geography
                Urban Geography
                Urban Areas
                Earth Sciences
                Geography
                Geographic Areas
                Urban Areas
                Social Sciences
                Archaeology
                Social Sciences
                Archaeology
                Historical Archaeology
                Earth Sciences
                Geography
                Human Geography
                Human Mobility
                Social Sciences
                Human Geography
                Human Mobility
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Population Density
                Custom metadata
                The data underlying the results presented in the study are available at https://core.tdar.org/project/392021/social-reactors-project-datasets.

                Uncategorized
                Uncategorized

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