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Scaling: lost in the smog

Abstract : The success of natural sciences lies in their great emphasis on the role of quantifiable data and their interplay with models. Data and models are both necessary for the progress of our understanding: data generate stylized facts and put constraints on models. Models on the other hand are essential to comprehend the processes at play and how the system works. If either is missing, our understanding and explanation of a phenomenon are questionable. This issue is very general, and affects all scientific domains, including the study of cities. Until recently, the field of urban economics essentially consisted in untested laws and theories, unjustified con-cepts that supersede empirical evidence [1]. Without em-pirical validation, it is not clear what these models teach us about cities. The tide has turned in recent years, however: the availability of data is increasing in size and specificity, which has led to the discovery of new stylized facts and opened the door to a new science of cities [2]. The recent craze for scaling laws [3–5], for instance, has been an important new step in the study of urban sys-tems. These laws present themselves as a power-law relation-ship between socioeconomic (GDP, number of patents), structural (length of roads, of cables) quantities Y , and the size of the population P of the city: Y = P
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Rémi Louf, Marc Barthelemy. Scaling: lost in the smog. Environment and Planning B: Planning and Design, SAGE Publications, 2014, 41, pp.767 - 769. ⟨10.1068/b4105c⟩. ⟨cea-01119056⟩

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