Numerous researchers from various disciplines have explored commonalities and divergences in the evolution of complex social formations. Here, we explore whether there is a characteristic time-course for the evolution of social complexity in a handful of different geographic areas. Time series data from the Seshat Global History Databank is shifted so that the overlapping time series can be fitted to a single logistic regression model for all 18 geographic areas under consideration. To analyse the endogenous growth of social complexity, each time series is restricted to a central time interval without discontinuous polity changes. The resulting regression shows convincing out-of-sample predictions and its period of rapidly growing social complexity can be identified via bootstrapping as a time interval of roughly 800 years.
翻译:多个不同学科的研究者已经探索了复杂社会形态演化的共性和差异。本文研究了在少数几个不同地理区域中,社会复杂性演化是否存在特征时间。利用Seshat全球历史数据库的时间序列数据,将重叠的时间序列进行平移,以便所有18个考虑地理区域的时间序列都能适配到一个单一的逻辑回归模型上。为了分析社会复杂性的内生增长,将每个时间序列限制在没有不连续的政治变化的中心时间间隔内。所得到的回归结果表现出令人信服的等外样本预测能力,通过自助法可将其在快速增长社会复杂性的时期识别为约800年的时段。