期刊
SCIENTIFIC REPORTS
卷 4, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/srep05393
关键词
-
资金
- Rockefeller Foundation [2011 SRC 108]
- James S. McDonnell Foundation [220020195]
- John Templeton Foundation [15705]
- Army Research Office Minerva Program [W911NF1210097]
- Bill and Melinda Gates Foundation [OPP1076282]
- U.S. Department of Energy through the LANL/LDRD Program [DE-AC52-06NA25396]
- FONDEF [D10I1038]
- Direct For Social, Behav & Economic Scie
- SBE Off Of Multidisciplinary Activities [1312294] Funding Source: National Science Foundation
- Bill and Melinda Gates Foundation [OPP1076282] Funding Source: Bill and Melinda Gates Foundation
Attempts to understand the relationship between diversity, productivity and scale have remained limited due to the scheme-dependent nature of the taxonomies describing complex systems. We analyze the diversity of US metropolitan areas in terms of profession diversity and employment to show how this frequency distribution takes a universal scale-invariant form, common to all cities, in the limit of infinite resolution of occupational taxonomies. We show that this limit is obtained under general conditions that follow from the analysis of the variation of the occupational frequency across taxonomies at different resolutions in a way analogous to finite-size scaling in statistical physical systems. We propose a theoretical framework that derives the form and parameters of the limiting distribution of professions based on the appearance, in urban social networks, of new occupations as the result of specialization and coordination of labor. By deriving classification scheme-independent measures of functional diversity and modeling cities as social networks embedded in infrastructural space, these results show how standard economic arguments of division and coordination of labor can be articulated in detail in cities and provide a microscopic basis for explaining increasing returns to population scale observed at the level of entire metropolitan areas.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据