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Indeed, [https://www.santafe.edu/people/profile/luis-bettencourt Luis Bettencourt], [[Geoffrey West]], and [https://sustainability-innovation.asu.edu/person/jose-lobo/ Jose Lobo]'s seminal work<ref name=":1" /> demonstrated that many urban indicators are associated with population size through a [[Power law|power-law]] relationship, in which socio-economic quantities tend to scale superlinearly<ref name=":2" />, while measures of infrastructure (such as the number of gas stations) scale sublinearly with population size<ref name=":3" />. They argue for a quantitative, predictive framework to understand cities as collective wholes, guiding urban policy, improving sustainability, and managing urban growth.<ref name=":0" />
The literature has grown, with many theoretical explanations for these emergent power-laws. Ribeiro and Rybski summarized these in their paper "[https://www.sciencedirect.com/science/article/abs/pii/S0370157323000650 Mathematical models to explain the origin of urban scaling laws]"<ref name=":4">{{Cite journal |last1=Ribeiro |first1=Fabiano L. |last2=Rybski |first2=Diego |date=2023 |title=Mathematical models to explain the origin of urban scaling laws |url=https://doi.org/10.1016/j.physrep.2023.02.002 |journal=Physics Reports |volume=1012 |pages=1–39 |doi=10.1016/j.physrep.2023.02.002 |bibcode=2023PhR..1012....1R |issn=0370-1573}}</ref>. Examples include Arbesman et al.'s 2009 model<ref>{{Cite journal |last1=Arbesman |first1=Samuel |last2=Kleinberg |first2=Jon M. |last3=Strogatz |first3=Steven H. |date=2009-01-30 |title=Superlinear scaling for innovation in cities |url=https://link.aps.org/doi/10.1103/PhysRevE.79.016115 |journal=Physical Review E |volume=79 |issue=1 |pages=016115 |doi=10.1103/PhysRevE.79.016115|pmid=19257115 |arxiv=0809.4994 |bibcode=2009PhRvE..79a6115A }}</ref>, Bettencourt's 2013 model<ref>{{Cite journal |last=Bettencourt |first=Luís M. A. |date=2013-06-21 |title=The Origins of Scaling in Cities |url=https://www.science.org/doi/10.1126/science.1235823 |journal=Science |language=en |volume=340 |issue=6139 |pages=1438–1441 |doi=10.1126/science.1235823 |pmid=23788793 |bibcode=2013Sci...340.1438B |issn=0036-8075}}</ref>, Gomez-Lievano et al.'s 2017 model<ref>{{Cite journal |last1=Gomez-Lievano |first1=Andres |last2=Patterson-Lomba |first2=Oscar |last3=Hausmann |first3=Ricardo |date=2016-12-22 |title=Explaining the prevalence, scaling and variance of urban phenomena |url=https://www.nature.com/articles/s41562-016-0012 |journal=Nature Human Behaviour |language=en |volume=1 |issue=1 |pages=1–6 |doi=10.1038/s41562-016-0012 |issn=2397-3374}}</ref>, and Yang et al.'s 2019 model<ref>{{Cite journal |last1=Yang |first1=V. Chuqiao |last2=Papachristos |first2=Andrew V. |last3=Abrams |first3=Daniel M. |date=2019-09-16 |title=Modeling the origin of urban-output scaling laws |url=https://link.aps.org/doi/10.1103/PhysRevE.100.032306 |journal=Physical Review E |volume=100 |issue=3 |pages=032306 |doi=10.1103/PhysRevE.100.032306|pmid=31639910 |arxiv=1712.00476 |bibcode=2019PhRvE.100c2306Y }}</ref>, among others (see <ref name=":4" />). The ultimate explanation of scaling laws observed in cities is still debated.<ref>{{Cite
== Key Concepts in Urban Scaling ==
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