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Can History Become a Real Science? Peter Turchin University of Connecticut Talk presented at Santa Fe, March 2007.

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Presentation on theme: "Can History Become a Real Science? Peter Turchin University of Connecticut Talk presented at Santa Fe, March 2007."— Presentation transcript:

1 Can History Become a Real Science? Peter Turchin University of Connecticut Talk presented at Santa Fe, March 2007

2 Main Points of the Talk Most historians, philosophers, and the lay public believe that there are no general laws of history I argue that the presence of strong empirical regularites implies the operation of general laws These laws can be discovered –there are much greater amounts of quantitative data on historical processes than might be expected but data sets are short and noisy

3 The Focus of the Talk is not on past accomplishments –too early for that! but on future directions –what I intend to work on during the next ~5 years

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5 No General Laws of History? Historical processes are too complex and too different from physical or biological ones (Karl Popper) Any explanation of the course of events is specific to there and then (the great majority of historians) "There are no general laws in history, apart from those imagined by their proponents" "History is just one damn thing after another"

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7 Ecosystems vs. Social Systems Both are very complex and heterogenous Organisms have a kind of free will –Insects, for example, are even less predictable than people At the micro level, ecosystems are a complete "mess" Yet, very clear patterns emerge at the macro level, such as population cycles –and there are laws of nature underlying these patterns

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9 Narrowing the focus: cliodynamics Large human collectives (10 5 ind) Long time scales: –a time step a human generation (20-30 y) –dynamics on multi-decadal and centennial scales A key role for mathematical models Quantitative variables, time-series data Patterns at a macro scale, but mechanisms at the individual level (There are other promising directions: social evolution, micro-scale ABS, etc)

10 Cliodynamics vs. Cliometrics Cliodynamics: from Clio (the muse of history) and dynamics (the study of temporally varying processes) –an explicit math component (models) Cliometrics: in general, quantification in history –statistical, not mechanism-oriented; lacks explicit theory-building approaches Synergism between the two approaches

11 Strong empirical patterns I Secular cycles: second-order dynamics The demographic-structural theory: a rapidly maturing theoretical framework for explaining secular cycles –verbal propositions translated into a suite of mathematical models –model predictions tested empirically for a variety of agrarian states strong effect of population pressure on real wages (Malthusian mechanism) strong effect of sociopolitical instability on population growth

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13 England: 1540-1870. Demographic data from Wrigley et al 1997 Instability data from quantification of narrative sources

14 Strong empirical patterns II: Religious Conversion Dynamics of many cases are well described by the logistic growth model Conversion to Islam –Iran –Spain Christianity The Church of Latter-Day Saints (Mormonism) - see Turchin 2003. Hist. Dynamics. Ch. 6

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18 Strong empirical patterns III: Spatial distribution of "imperiogenesis" Database: largest territorial polities –excluding modern sea-based empires Source: Taagepera, supplemented Cut-off point: area 1 Mm 2 at peak More than 60 such polities are known –only 1 (Inca) outside Afroeurasia

19 M Egypt Axum Fatim Almorav Almohad Mali Mam Hsnu Juan Turk Uig Tufan Khazar Hsi Khorezm Kara-Kh Mongol GoldenH Chagatai Timur Shang Han Tang Liang Liao Sung Jur Ming Manchu Rom Huns Frank Kiev Lith-Pol Osman Russia Srivi Khmer Maur Kushan Gupta Harsha Delhi Mughal Mar Assyr Med Ach Sas Sele Parth Caliph Selj Sam Buy Ghazn Ayy Il-Kh Byz

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21 Largest territorial polities tend to arise at interfaces between settled and nomadic societies Not a strict "law", but rather a statistical correlation Several "hotspots" of imperiogenesis and upsweeps in max. territorial size –Mesopotamia and Iran –Northern India –Northern China

22 UnificationPeriodEthnicityFromCapital Shang1766–1122 BCE ??NC (Huang He)Anyang (Huang-He) W. Zhou1122­–771 BCEFrontier Han (Western Barbarians) NW (Wei River Valley) Loyang (Huang He) Qin221–206 BCEFrontier HanNW (Wei River Valley) Xianyang (Wei) Han202 BCE–220HanNW (looks like their base was at the confluence of Wei and Huang) Changan (Wei) N. Wei (partial, N) 386–534To-ba (Turkic)NWLoyang (Huang He) Sui581–618HanNW (Wei River Valley) Changan (Wei) Tang618–907Han (ruling family of Turkish descent) NW (Wei RV?)Changan (Wei)

23 Liao (partial, N) 907–1125Khitan (Altaic?) NEBeijing N. Sung (partial, w/o N) 960–1127HanNC (from lower Huang He area around Kaifeng) Kaifeng (Huang He) Jin (partial, N) 1115–1234Jurchen (Tungus) NEBeijing Yuan1206–1368MongolNW (Mongolia)Beijing Ming1368–1644HanCS (from Nanjing area): the only unification not from N Beijing Qing1644–1911Manchu (Tungus) NEBeijing Communist1949–HanNW (Long March to Wei River Valley; unification from there) Beijing

24 The East Asian Imperiogenesis Hotspot: Empirical Patterns 14 unifications of China from the Shang to Communist eras (some partial) –(E.N. Anderson, supplemented) Summary: –8 unifications from NW (usually, Wei RV) –3 unifications from NE (Liao, Manchuria) –2 unifications from NC (Huang He) –1 unification from SC (Nanjing)

25 The broad context: The puzzle of human ultrasociality Evolution of cooperation in small groups (~10 2 ind) by group selection is essentially understood –D.S. Wilson, Boyd, Richerson, Bowles Asabiya (Ibn Khaldun): capacity for collective action But how did huge groups of 10 6 10 8 cooperating individuals arise?

26 The "Mirror Empires" Model A steppe frontier between settled agriculturalists and nomadic pastoralists Starting point: small-scale polities on both sides of the frontier Pastoralists enjoy preponderance of military power; need the products of agriculture

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31 Outcome An agrarian empire and a nomadic imperial confederation arise simultaneously in a mirror fashion The process occurs in a series of steps of increasing territorial size and social complexity A positive feedback loop (self-feeding process) Runaway territorial growth is eventually stopped by space or logistic limits

32 Two Kinds of Sciences (Randall Collins, The Sociology of Philosophies) "Rapid Discovery""Traditional" Rapid rate of knowledge production Slow rate of knowledge production ConsensusDissensus Priority disputes; simultaneous discovery frequent Disputes focus on clashing ideologies Nobody reads the founders The founders are constantly re-examined and re-appraised

33 Can cliodynamics become a "rapid discovery science"? In the end, this is an empirical issue: "the proof is in the pudding" We have to generate a constant flow of new results We need to propose and defend candidates for general laws So what about the data?

34 Sources of data Archaeological Skeletal material Coin hoards Quantification of narrative sources and many, many other

35 Novgorod the Great

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40 Stature as a proxy for population density Abundance of data (10 6 skeletons) Human height is a very sensitive indicator of nutrition conditions –a proxy for population pressure But temporal resolution is poor –Radiocarbon dating errors are ~ 50 y –However, given the abundance of data, it should be possible to use statistical methods for error reduction

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42 Skeletons, cont. Can be used to score the intensity of interpersonal violence, and thus, indirectly, sociopolitical instability Example: the study of Tim Kohler et al in the American Southwest

43 Figure 4. Graph of standardized, smoothed population (N, black) superimposed on smoothed warfare frequency (W, red). (Kohler et al. 2006)

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45 Coin hoards Abundant in many historical eras; datable Frequency of hoards (per decade) reflects conditions of internal disorder: –people bury hoards in times of danger –most emergency hoards are recovered, except when the owner is unable to do so Caveat: –hoard incidence reflects not only internal disorder, but also catastrophic external invasions

46 Coin Hoards: Republican Rome, 230-0 BCE (Michael Crawford)

47 Instability in Republican Rome, from narrative sources

48 Coin Hoards and the Instability Index

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51 Quantifying sociopolitical instability from narrative sources Sociopolitical instability: –state collapse, peasant uprisings, civil wars, and other instances of major internal disturbances Construct an annual index by noting which years had an instability event, and which years did not (either 0 or 1) A decadal index = the number of instability years per decade (varies between 0 & 10)

52 yearsDescription 1138-53Anarchy (civil war between Stephen and Matilda/Henry) 1173-4Uprising of Henry the Younger. Rebellion of several English earls. 1215-7Civil war (Magna Carta) 1232Revolt against papal collectors 1233Richard Marshal rebelled and was murdered in Ireland 1263-7Civil war: barons against the king 1315Civil disorders during supremacy of Lancaster (1314-22) 1321-2Civil war. Baron uprising in the western counties. 1326-7Rebellion of Isabella and Mortimer. Edward II deposed, murdered in prison 1330Edward III led the baronial opposition to Mortimer (hanged, 1330) 1381Peasants' Revolt 1387-8Insurrection of the Lords Appelant 1391Coup detat of Richard II 1397-9Events leading to the deposition of Richard II (1399). 1400-8Glyn Dwr rebellion 1414A Lollard plot against the king's life 1448-51Domestic disorders 1450Jack Cade's rebellion

53 yearsDescription 1455-6The Wars of Roses: 1st phase 1460-5The Wars of Roses: 2nd phase 1467-71The Wars of Roses: 3rd phase 1483-5The Wars of Roses: 4th phase 1495Rebellion of Perkin Warbeck 1497Insurrection in Cornwall 1536-7Pilgrimage of Grace 1549Ketts rebellion 1554Wyatts rebellion 1569Rebellion of catholic lords of the North 1639-40The Bishops Wars 1642-7Civil War 1648-51Second Civil War 1655Penruddock rising in Salisbury 1660Monks coup; restoration of James II 1666Revolt of Scottish Covenanters 1679Revolt of Scottish Covenanters 1685Monmouth and Argyll rebellions 1687-92Glorious Revoultion, with intervention by France 1715-6Jacobite rebellion in Scotland 1745-6Scottish rising (Jacobite pretender)

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56 "Wheels within Wheels" Two kinds of oscillations superimposed: Secular cycles –periods = 200300 y, or ~10 generations (second-order dynamics) "Fathers-and-sons cycles" –periods = 4060 y, or ~2 generations (first-order dynamics)

57 Main Points of the Talk Most historians, philosophers, and the lay public believe that there are no general laws of history I argue that the presence of strong empirical regularites implies the operation of general laws These laws can be discovered –there are much greater amounts of quantitative data on historical processes than might be expected but data sets are short and noisy


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