Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization
Ter Haar, B
Proceedings of the National Academy of Sciences
National Academy of Sciences
Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as "Seshat: Global History Databank." We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history.
This work was supported by a John Templeton Foundation grant to the Evolution Institute, entitled "Axial-Age Religions and the Z-Curve of Human Egalitarianism," a Tricoastal Foundation grant to the Evolution Institute, entitled "The Deep Roots of the Modern World: The Cultural Evolution of Economic Growth and Political Stability," an ESRC Large Grant entitled "Ritual, Community, and Conflict" (REF RES-060-25-0085), an Advanced Grant from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement No. 694986), and a grant from the European Union’s Horizon 2020 research and innovation programme (grant agreement No 644055 [ALIGNED, www.aligned-project.eu]).
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.
Vol. 115 (2), E144 - E151
Place of publication