Journal of Social Computing


hierarchy, scalar stress, Seshat Databank, multiple imputation, multiple regression


Although Gregory Johnson’s models have influenced social theory in archaeology, few have applied or built upon these models to predict aspects of social organization, group size, or fissioning. Exceptions have been limited to small case studies. Recently, the relationship between a society’s scale and its information-processing capacities has been explored using the Seshat Databank. Here, I apply multiple-linear regression analysis to the Seshat data using Turchin and colleagues’ 9 “complexity characteristics” (CCs) to further examine the relationship between the hierarchy CC and the remaining 8 CCs which include both aspects of a polity’s scale and aspects of what Kohler et al. call “collective computation”. The results support Johnson’s ideas that stratification will generally increase with increases in a polity’s scale (population, territory); however, stratification is also higher when polities increase their developments in information-processing variables such as texts.