Peter Turchin, University of Connecticut
Harvey Whitehouse, University of Oxford
Pieter François, University of Oxford
Daniel Hoyer, Evolution Institute
Abel Alves, Ball State University
John Baines, University of Oxford
David Baker, Macquarie University
Marta Bartkowiak, Adam Mickiewicz University, Poznań
Jennifer Bates, Brown University
James Bennett, University of Washington
Julye Bidmead, Chapman UniversityFollow
Peter Bol, Harvard University
Alessandro Ceccarelli, University of Cambridge
Kostis Christakis, British School at Athens
David Christian, Macquarie University
Alan Covey, University of Texas
Franco De Angelis, University of British Columbia
Timothy K. Earle, Northwestern University
Neil R. Edwards, Open University
Gary Feinman, Field Museum
Stephanie Grohmann, University of Edinburgh
Philip B. Holden, Open University
Árni Júlíusson, University of Iceland
Andrey Korotayev, National Research University Higher School of Economics
Axel Kristinsson, Independent Scholar
Jennifer Larson, Kent State University
Oren Litwin, George Mason University
Victor Mair, University of Pennsylvania
Joseph G. Manning, Yale University
Patrick Manning, University of Pittsburgh
Arkadiusz Marciniak, Adam Mickiewcz University, Poznan
Gregory McMahon, University of New Hampshire
John Miksic, National University of Singapore
Juan Carlos Moreno Garcia, French National Centre for Scientific Research
Ian Morris, Stanford University
Ruth Mostern, University of Pittsburgh
Daniel Mullins, Birkbeck University of London
Oluwole Oyebamiji, Lancaster University
Peter Peregrine, Lawrence University
Cameron Petrie, University of Cambridge
Johannes Preiser-Kapeller, Austrian Academy of Sciences
Peter Rudiak-Gould, Independent Scholar
Paula Sabloff, Santa Fe Institute
Patrick Savage, Keio University
Charles Spencer, American Museum of Natural History
Miriam Stark, University of Hawaii at Manoa
Barend ter Haar, University of Hamburg
Stefan Thurner, Complexity Science Hub, Vienna
Vesna Wallace, University of California, Santa Barbara
Nina Witoszek, University of Oslo
Liye Xie, University of Toronto

Document Type

Article

Publication Date

11-6-2020

Abstract

This article introduces the Seshat: Global History Databank, its potential, and its methodology. Seshat is a databank containing vast amounts of quantitative data buttressed by qualitative nuance for a large sample of historical and archaeological polities. The sample is global in scope and covers the period from the Neolithic Revolution to the Industrial Revolution. Seshat allows scholars to capture dynamic processes and to test theories about the co-evolution (or not) of social scale and complexity, agriculture, warfare, religion, and any number of such Big Questions. Seshat is rapidly becoming a massive resource for innovative cross-cultural and cross-disciplinary research. Seshat is part of a growing trend to use comparative historical data on a large scale and contributes as such to a growing consilience between the humanities and social sciences. Seshat is underpinned by a robust and transparent workflow to ensure the ever growing dataset is of high quality.

Comments

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Journal of Cognitive Historiography, volume 5, issue 1-2, in 2020 following peer review. The definitive publisher-authenticated version is available online at https://doi.org/10.1558/jch.39395 .

Peer Reviewed

1

Copyright

Equinox Publishing

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