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Scaling human sociopolitical complexity.
Hamilton, Marcus J; Walker, Robert S; Buchanan, Briggs; Sandeford, David S.
Afiliación
  • Hamilton MJ; Department of Anthropology, University of Texas at San Antonio, San Antonio, TX, United States of America.
  • Walker RS; Department of Anthropology, University of Missouri, Columbia, MO, United States of America.
  • Buchanan B; Department of Anthropology, University of Tulsa, Tulsa, OK, United States of America.
  • Sandeford DS; School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, United States of America.
PLoS One ; 15(7): e0234615, 2020.
Article en En | MEDLINE | ID: mdl-32614836
Human societies exhibit a diversity of social organizations that vary widely in size, structure, and complexity. Today, human sociopolitical complexity ranges from stateless small-scale societies of a few hundred individuals to complex states of millions, most of this diversity evolving only over the last few hundred years. Understanding how sociopolitical complexity evolved over time and space has always been a central focus of the social sciences. Yet despite this long-term interest, a quantitative understanding of how sociopolitical complexity varies across cultures is not well developed. Here we use scaling analysis to examine the statistical structure of a global sample of over a thousand human societies across multiple levels of sociopolitical complexity. First, we show that levels of sociopolitical complexity are self-similar as adjacent levels of jurisdictional hierarchy see a four-fold increase in population size, a two-fold increase in geographic range, and therefore a doubling of population density. Second, we show how this self-similarity leads to the scaling of population size and geographic range. As societies increase in complexity population density is reconfigured in space and quantified by scaling parameters. However, there is considerable overlap in population metrics across all scales suggesting that while more complex societies tend to have larger and denser populations, larger and denser populations are not necessarily more complex.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Política / Ciencias Sociales / Densidad de Población / Modelos Organizacionales Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Política / Ciencias Sociales / Densidad de Población / Modelos Organizacionales Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos
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