Growth, innovation, scaling, and the pace of life in cities.¶
Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C., & West, G. B. (2007). Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences, 104(17), 7301-7306.
Cited by¶
4 citations across 4 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Allometry and Scaling Law
- Crime rate, disease transmission, and social interactions scale nonlinearly with city size, as Bettencourt, Lobo, Helbing, Kühnert, and West (2007) established empirically across global urban systems.
SupportedVerified against the work's full text
The paper reports power-law scaling with city size for crime rates, infectious-disease spread and walking speed, attributing superlinear scaling to social interactions across urban systems.
“Quantitative confirmation is provided by urban crime rates ( 42 ), rates of spread of infectious diseases such as AIDS, and even pedestrian walking speeds ( 30 ), which, when plotted logarithmically, exhibit power law scaling”
- Crime rate, disease transmission, and social interactions scale nonlinearly with city size, as Bettencourt, Lobo, Helbing, Kühnert, and West (2007) established empirically across global urban systems.
- Diseconomies of Scale
- The prime names that crossover and asserts that it is not an accident of bad management but a structural feature of systems whose connective tissue grows faster than their productive tissue.
This sourceEmpirically establishes superlinear scaling of urban quantities with population, formalizing the rate/exponent claim that when one quantity scales with a higher exponent than another a crossover is structurally inevitable, and that the served-quantity-outruns-serving-capacity pattern recurs across firms, organisms, and cities.
Supported in partVerified against the work's full text
Supplies a growth model where maintenance needs outrun sublinearly scaling resources, capping organisms and economy-of-scale organizations; no teams, firms' MES, or urban congestion.
“This solution is characteristic of biological systems where the predictions of Eq. 2 are in excellent agreement with data ( 41 ). Thus, cities and, more generally, social organizations that are driven by economies of scale are destined to eventually stop growing”
- The prime names that crossover and asserts that it is not an accident of bad management but a structural feature of systems whose connective tissue grows faster than their productive tissue.
- Economies of Scale
- In research organizations, large national laboratories (CERN, NIH, Argonne) spread the fixed cost of extraordinarily expensive shared instruments across many user groups, which is economies of scale in scientific infrastructure — kindred in form to the urban-scaling laws Bettencourt, Lobo, Helbing, Kühnert, and West (2007) documented, where shared metropolitan infrastructure shows sublinear per-capita cost as population grows.
This sourceDemonstrates sublinear (β ≈ 0.85) scaling of physical infrastructure with city population — shared metropolitan infrastructure showing declining per-capita cost as population grows.
Supported in partVerified against the work's full text
Bettencourt et al. back the urban half: infrastructure scales sublinearly (beta about 0.8) with city size, but they say nothing about national laboratories or per-capita cost.
“characterizes material quantities displaying economies of scale associated with infrastructure, analogous to similar quantities in biology”
- In research organizations, large national laboratories (CERN, NIH, Argonne) spread the fixed cost of extraordinarily expensive shared instruments across many user groups, which is economies of scale in scientific infrastructure — kindred in form to the urban-scaling laws Bettencourt, Lobo, Helbing, Kühnert, and West (2007) documented, where shared metropolitan infrastructure shows sublinear per-capita cost as population grows.
- Scaling and Scale Dependence
- The underlying mechanism—fundamental shifts in dominant constraints and mechanisms—is domain-invariant, a cross-substrate transfer Bettencourt, Lobo, Helbing, Kühnert, and West (2007) demonstrated empirically by showing that diverse urban properties scale as power laws with population across nations and eras.
This sourceEmpirical demonstration that diverse urban properties (patents, wages, crime, infrastructure) scale as power laws with population across nations and historical periods, providing strong cross-substrate evidence that scale-dependence patterns transfer across domains.
Supported in partVerified against the work's full text
Supports the empirical half: urban indicators scale as power laws with population across nations and time; the "domain-invariant constraint-shift mechanism" is not in the paper.
“We find robust and commensurate scaling exponents across different nations, economic systems, levels of development, and recent time periods for a wide variety of indicators.”
- The underlying mechanism—fundamental shifts in dominant constraints and mechanisms—is domain-invariant, a cross-substrate transfer Bettencourt, Lobo, Helbing, Kühnert, and West (2007) demonstrated empirically by showing that diverse urban properties scale as power laws with population across nations and eras.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 4 of 4 citations: 1 supported, 3 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
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