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  • Civilizations as dynamic networks Cities, hinterlands, populations, industries, trade and conflict

    Douglas R. White 2005 All rights reserved

    50 slides - also viewable on drw conference paper website version 1.3 of 11/12/2005European Conference on Complex Systems Paris, 14-18 November 2005

  • acknowledgementsThanks to the International Program of the Santa Fe Institute for support of the work on urban scaling with Nataa Kejar and Constantino Tsallis, and thanks to the ISCOM project (Information Society as a Complex System) principal investigators David Lane, Geoff West, Sander van der Leeuw and Denise Pumain for ISCOM support of collaboration with Peter Spufford at Cambridge, and for research assistance support from Joseph Wehbe. Also thanks to David Krakauer and Luis Bettencourt at SFI in suggesting how our multilayered models of rise and fall of city networks could be guided by sufficient statistics modeling principles and to Lane and van der Leeuw for suggestions on the slides. This study is complemented by others within the ISCOM project concerned with urban scaling and innovation and draws several slides from those projects.Thanks to Peter Spufford for his generous support in providing systematic empirical data on intercity networks and industries in the medieval period to complement the data in his book, Dean Anuska Ferligoj, School of Social Sciences, University of Ljubljana, for five weeks of support for work carried out with Kejar in Ljubljana in summer, 2005, Cline Rozenblat (ISCOM project) for providing the historical urban size data, and Camille Roth (Polytechnic, Paris) for collaborations on representing evolutions of multiple industries across city netwks. A jointly authored on this project is in draft with Spufford and possibly others.

  • some main approaches and areas of findings1 Urban scaling: distributional scaling and historical transitionsCity functions (Geoff West , Luis Bettencourt, Jos Lobo 2005)City growth and inequality parameters: From Zipf's rank size laws to power laws to a stronger scaling theory of q-exponentialsPeriodizing: Historical q-periods and their correlatesCommercial vs. Financial capital and organizationMarket equilibrium vs. Structural Inflation

    2 Rise and fall of intercity networks (e.g., trade and conflict)Key concept: structural cohesion and its effects, such as market zones and price equilibrium vs. inflation in cohesive cores versus peripheries (White and Harary 2002 SocMeth, Moody and White 2003 ASR)Similarly, effects of network betweenness versus flow centrality on commercial vs. financial capital and institutional organization

    3 Interactive dynamics: world population, cities and hinterlands, polities economic growth versus sociopolitical conflictorganizational change at macro level and micro level.Outline re: civilizations as dynamic networksGeneral approach: interactive multi-nets, networks among and between different types of entities in time series with changing links and attributes

  • City Networks Routes, Capacities Velocities and Magnitudes of trade Organizational transformationof nodesSTATES MARKETSfrom factions & coalitions from structurally cohesiveto sovereignty - emergent k-components - emergent Spatiopolitical units Network units (overlap)Co-evolution time-series of Cities and City NetworksInterference and attempts at regulationSources of boundary conflictsbeginperiodize

  • Geoff West, Luis Bettencourt, Jos Lobo. 2005 (Pace of City Life):Innovation-Dependent (Superlinear), Linear, and Scale-Efficient (Sublinear) Power LawsUrban Scaling: Functions

    Chart4

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    15488.16618912487161.4341021296080.93000323185057.8972712995

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    851.1380382024153.1087461682494.2765473285858.9541935788

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    46.77351412873.273406948840.1763061093145.8713507001

    10.96478196140.478630092311.454338263860.1132217309

    R&Dchina-superlinear

    R&Dfrance-superlinear

    Elec.Cons.-linear

    Gas Sales-sublinear

    City Sizes

    City Functions

    Sheet1

    city size binsR&Dchina-superlinearR&Dfrance-superlinearElec.Cons.-linearGas Sales-sublinear

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    0.00010.00000010.00050.05

    Sheet1

    R&Dchina-superlinear

    R&Dfrance-superlinear

    Elec.Cons.-linear

    Gas Sales-sublinear

    City Sizes

    City Functions

    Sheet2

    Sheet3

  • Superlinear ~ 1.67

    Linear ~ 1

    Sublinear ~ .85ISCOM working paper

  • (White, Kejar, Tsallis, and Rozenblat 2005 working paper)the next few slides compare the scale K and coefficients of the power-law y(x) K x- (and Pareto = +1) with the q-exponential parameters for q slope and scale in y(x) ~ [1 + (1q) x/)]1/(1q), fitted to entire size curvesNot a good fit to overall city size distributions Power laws and Zipfs law might fit upper bin frequencies for city sizes but not the whole curveinset: y = cumulative number of people in these cities

    Dashed line = portion of distribution that is "power-law (but is exaggerated in the upper bins)Horizontal axis x = binned (logs of city size)Vertical axis y = cumulative number

    of cities at this log bin or higherUrban Scaling: City Sizes=1=2Example: 1950 United Nations data for world cities

    Chart1

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    ncities

    Chart5

    577200000

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    tot

    date50637910012615920025231840050463580010081270160020162540320040325080640080641016012800161272031925600

    1950287115265208245726223431209364186790165381144976117809109018958706471964719451132870721160

    1950293217283983272402257022236472211141188162167175141475125822102938829277204449418279922107212339

    19553603933557063495063398813262663117642889772596382305082099771830401505131300101122999118677243378393097313220

    1960430122426190419922411583399055380823360078330222288205258369237243204990161657145015123796105617700464311025140

    1965500269495157486923473979455534435151398895357564318628286942257007208097177380149412130532105971478923899228120

    19705708915589735404595151854836584370263824633541483053892686372172171738551738551466481123054381332659

    19756483596389546238355989335579635011964459444120813629673156382674402167931721161721161218905833035651

    1980713963688148643316586943518391476108429945368279314305272913223042193878165237755795134321854

    19857859307421676789346001875390124884554349543645753132352678882279091853201110956738123322

    19909044128648707995067082986347475748865079384282953585063148612682492159551622658467925069

    1995102319510039199274068369477556016755266046235098404320003618083281852792581952281051087638626959

    2000113552610769009843188838458002587051206100395062964396303779903144962763311522259853528025

    200512188361136525102988793748881498672427659032852055143978837495532283023108712079549531

    2010134458012691881176934107093193784782011171270658931552689344065636045029128417893273449

    2015139376613181131208480106732993350379237567808659471