Changes in agglomeration and productivity are poor predictors of inequality across the archaeological record
Abstract
We address three basic issues regarding the long-term dynamics of inequality in society. First, we consider the interpretation of residence sizes in socioeconomic terms by comparing statistical patterns extracted from the Global Dynamics of Inequality (GINI) Project database with those from the 21st-century United States. Second, we examine the degree to which the size and productivity of human networks is systematically related to inequality. Finally, we investigate relationships between productivity and productivity growth distributions for patterns of inequality and development across preindustrial societies. We find that across preindustrial societies residence size distributions provide a reasonable proxy for the distribution of productivity (income, a flow of physical and social resources to the group) and a minimum estimator for the distribution of wealth (a stock of such resources accumulated over time); that scale and productivity affect levels of inequality but account for only a small fraction of the observed variance across societies; and that inequality growth is independent of productivity growth, on average and over time. These findings have important implications for efforts to promote more equitable economic development in the present.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (9)
Scott G. Ortman
Santa Fe Institute
Amy Bogaard
Santa Fe Institute
Jessica Munson
Department of Anthropology-Sociology, Lycoming College
Dan Lawrence
Department of Archaeology, Durham University
Adam S. Green
Department of Archaeology, University of York
Gary M. Feinman
Negaunee Integrative Research Center, Field Museum of Natural History
Shadreck Chirikure
Research Laboratory for Archaeology and the History of Art, School of Archaeology, University of Oxford
Johannes H. Uhl
Institute of Behavioral Science, University of Colorado Boulder
Stefan Leyk
Institute of Behavioral Science, University of Colorado Boulder