Clio Meets Seshat:Building the Global History

Database

Peter TurchinDublin, June 2014

A Science of History?• According to most historians, history

is a part of the humanities• Most historians have abandoned the

belief in general laws• Yet, when historians construct

narratives they also propose explanations for why things happened the way they did– which implies existence of general

principles (“laws”)

History as viewed by a natural scientist

• A mature descriptive discipline that requires high technical expertise

• But it is not (yet) a theoretical, explanatory science

• History needs– a falsificationist agenda– a mathematical component– systematic databases for testing models

Why History Needs Mathematics• A science becomes Science only after

it gains mathematical content– formal models– statistical analysis

• Why: to translate assumptions into predictions (for empirical testing)– especially in nonlinear dynamics

• Explicit mathematical models can correct faulty verbal theory– example: the theory of “imperial

overstrech”

Imperial Overstrech: the Theory

• An empire gobbles up too much territory, incurs heavy logistical burdens that cause it to collapse– Paul Kennedy– Randall Collins

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Conclusion: theory of imperial overstretch leads to a first-order differential equation that cannot exhibit boom-bust dynamics

exp[ / ]dA

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predicted dynamics

Why do Empires Fall?

“My name is Ozymandias, king of kings...”

“The Decline and Fall of the Roman Empire”

Why did the Roman Empire Fall?

• The German historian Alexander Demandt counted at least 210 explanations of why Rome fell

• Demandt, A. 1984. Der Fall Roms: die Auflösung des Römischen Reiches im Urteil der Nachwelt (Beck, Munich)

• The problem with history, as it is traditionally practiced, is that theories multiply but are never rejected

… and explanations continue to multiply…

Can ancient history tell us

anything about today?

Why we need to startreject hypotheses

• In natural sciences progress occurs when some hypotheses/theories are rejected in favor of others– Phlogiston– Lamarkism

The Good Old Scientific Method

• Define the question• Propose two or more alternative

explanations/theories• Use mathematical models to extract

predictions from theories– predictions that disagree about some

observable aspect of reality

• Put together data to adjudicate between the theories

• Repeat as necessary

The Puzzle of Ultrasociality

• Ultrasociality – extensive cooperation among very large numbers of genetically unrelated individuals

• How did it evolve?

International Space Station

Approaches:• General theory: cultural multilevel

selection (CMLS) of ultrasocial norms and institutions

• A specific model: Africa and Eurasia, 1500 BCE – 1500 CE

• Empirical tests: building a massive historical database of cultural evolution

General Theorydefinitions

• Ultrasociality: extensive cooperation among very large numbers (e.g. >106) of genetically unrelated individuals

• Norms: culturally acquired rules of behavior

• Institutions: systems of norms that govern behavior of individuals in specific contexts

• Ultrasocial norms and institutions: provide the basis for integration of large-scale societies, but have costs for lower-level units

Examples of ultrasocial norms

• Propensity to trust and help individuals outside one’s ethnic group (“generalized trust”)– benefit: provides a basis for cooperation in

multiethnic societies– cost: vulnerability to free-riding by ethnic

groups that restrict cooperation to coethnics• Willingness to pay national taxes• Obeying laws• Refusing bribes and not offering bribes• Volunteering for military service in times of

war

Examples of ultrasocial institutions

• Government by professional bureaucracies– basis for one common definition of the state– benefit: governing sufficiently large-scale

societies is apparently impossible without bureaucrats, record-keeping, division of tasks

– cost: expensive to train and maintain bureaucrats; principal-agent problems

• Universal religions and other integrative ideologies

• Legitimating power/restraining rulers• The state as a ‘bundle’ of ultrasocial

institutions

Understanding how ultrasocial traits spread

• is not a simple matter of accounting for their benefits for integration of large-scale societies

• these institutions have significant costs– and historical record indicates that they

repeatedly collapsed

• need an evolutionary mechanism to explain the spread of such traits despite the costs

• CMLS: cultural multilevel selection – “group selection” – Boyd, Richerson, D.S. Wilson, Bowles, Turchin

Major Evolutionary Transitions:

• Eukaryotic cell• Multicellular organism• Eusocial insect colony• Complex human society

• General Processes– “particle” cooperation– selection on “collectives”– suppression of particle selfishness

and competition– increasing functional integration

of collectives– collectives become organisms

A Social Scale (Agrarian Polities)

Population Area, km2 Polities

10,000,000s 1,000,000s Mega-empires

1,000,000s 100,000s Macrostates

100,000s 10,000s States (Archaic), Supercomplex chiefdoms

10,000s 1,000s Complex chiefdoms, City states

1,000s 100s Simple chiefdoms,acephalic tribes

100s Local communties (villages)

Alternative Theories

• Resource base (agriculture)– Childe, White, Service, Diamond

• Social differentiation and class structure– Marx, Engels, Patterson

• Warfare and circumscription - Carneiro

• Cultural Multilevel Selection– Boyd, Richerson, D.S. Wilson, Bowles

• Economics and trade, problem-solving and information processing, …

Real Data

Simulated Data

Overall model fitR2 ≈ 0.65

Spread of ultrasocial traits predicted by the model

SESHAT: Global History DatabankThe huge corpus of knowledge about past societies collectively possessed by academic historians is almost entirely in a form that is inaccessible to scientific analysis, stored in historians’ brains or scattered over heterogeneous notes and publications. The huge potential of this knowledge for testing theories about political and economic development has been largely untapped.

Our goal: a historical database that will enable us and others to test theories about the processes responsible for the rise of large-scale societies in human history. The database will bring together, in a systematic form, what is currently known about the sociopolitical organization of human societies, and how it has evolved with time.

An example: bureacracy

characteristics• Examination system• Merit promotion• Solutions to the

principal-agent problem

SESHAT: Global History DatabankEditorial BoardPeter Turchin (UConn): overall coordinator; social complexityHarvey Whitehouse (Oxford): co-editor; ritual and religionPieter François (Oxford): historical coordinator; ritual variablesThomas Currie (Exeter): resources, agriculture, and populationKevin Feeney (TCD): information technology

ConsultantsJ. G. Manning (Yale)Douglas White (UC Irvine)Arkadiusz Marciniak (Poznan)Peter Peregrine (Lawrence and Santa Fe Institute)Enrico Spolaore (Tufts) David Sloan Wilson (Binghamton)Peter Richerson (UC Davis)

PostdocsDaniel Hoyer, and 2 postdocs to be hired

Research AssistantsRudolf Cesaretti, Edward Turner, and ~10 short-term RAs

Data Consumers

Community of experts & volunteers

Electronic Archives

What will Seshat (eventually) do?

databases

SeshatDatabank

Collective intelligence

High Quality OpenData

Feedback

“improve the extraction of collective intelligence from electronic archives,

research communities and data consumers to improve the quality of published data”

SESHAT: Global History Databank

Acknowledgments

Bernard WinogradJim Bennett

Tricoastal Foundation