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dc.coverage.spatialLONDON
dc.creatorBettencourt, Luis M.A.
dc.creatorSamaniego-Salinas, Horacio Augusto
dc.creatorYoun, Hyejin
dc.date.accessioned2017-04-27T18:50:11Z
dc.date.available2017-04-27T18:50:11Z
dc.date.issued2014
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10533/197048
dc.description.abstractAttempts 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.
dc.language.isoENG
dc.publisherNATURE PUBLISHING GROUP
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.relation.urihttps://doi.org/10.1038/srep05393
dc.titleProfessional diversity and the productivity of cities
dc.typeArticulo
dc.identifier.folioD10I1038
dc.country.isoGBR
dc.description.citasisi3
dc.description.conicytprogramFONDEF
dc.description.emailhoracio@ecoinformatica.cl
dc.description.investmentarticleRockefeller 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]
dc.identifier.isiWOS:000337888600007
dc.relation.projectidinfo:eu-repo/grantAgreement/Fondef/D10I1038
dc.relation.setinfo:eu-repo/semantics/dataset/hdl.handle.net/10533/93477
dc.rights.driverinfo:eu-repo/semantics/openAccess
dc.title.journalSCIENTIFIC REPORTS
dc.title.journalabbreviationSci Rep
dc.type.driverinfo:eu-repo/semantics/article
dc.description.shortconicytprogramFONDEF
dc.identifier.eissn0
dc.description.agradWe thank Doug Erwin, Ricardo Hausmann, Cesar Hidalgo, Jose Lobo and Geoffrey West for discussions. This research was partially supported by the Rockefeller Foundation (grant no. 2011 SRC 108), the James S. McDonnell Foundation (grant no. 220020195), the John Templeton Foundation (grant no. 15705), the Army Research Office Minerva Program (grant no. W911NF1210097), the Bill and Melinda Gates Foundation (grant OPP1076282), the U.S. Department of Energy through the LANL/LDRD Program (contract no. DE-AC52-06NA25396), and a FONDEF grant (D10I1038).
dc.type.openaireinfo:eu-repo/semantics/publishedVersion


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