Organizational complexity and demographic scale in primary states

Area of Science:

• Cross-disciplinary research at the intersection of natural and social sciences.
• Focus on social evolution, anthropology, and network science.

Background:

• The relationship between organizational complexity and demographic scale is a key problem in social evolution.
• Existing anthropological models assume population growth drives complexity, but this link lacks formalization and cross-cultural validation.
• A rich dataset exists for 10 primary state formation cases, but it is unsystematized.

Purpose of the Study:

• To formalize and cross-culturally validate the relationship between organizational complexity and demographic scale in state societies.
• To propose and test a complex network model for understanding the evolution of social organizations.

Main Methods:

• Utilized a dataset of diachronic organizational and demographic data from 10 archaeologically known cases of primary state formation.
• Developed and tested a complex network model representing state societies as discrete, self-similar, hierarchical social networks.

Main Results:

• The proposed complex network model accurately describes the relationship between organizational complexity and population scale across all 10 cases.
• The findings support the model's architecture for understanding state societies.

Conclusions:

• The complex network architecture of state societies provides a robust framework for understanding their development.
• Further research into human nature's role in social evolution, informed by this network perspective, may advance understanding of modern social organization.