Explaining the rise of moralizing religions: a test of competing hypotheses using the Seshat Databank

• DOI: 10.1080/2153599x.2022.2065345
• Publication Date: 2022-07-01T03:25:40Z
• Authors: Peter Turchin; Harvey Whitehouse; Jennifer Larson; Enrico Cioni; Jenny Reddish; Daniel Hoyer; Patrick E. Savage; R. Alan Covey; John Baines; Mark Altaweel; Eugene Anderson; Peter Bol; Eva Brandl; David M. Carballo; Gary Feinman; Andrey Korotayev; Nikolay Kradin; Jill D. Levine; Selin E. Nugent; Andrea Squitieri; Vesna Wallace; Pieter François
• Keywords: bepress|Social and Behavioral Sciences|Anthropology; 2. Zero hunger; 0303 health sciences; 330; evolution of social complexity; SocArXiv|Social and Behavioral Sciences|Anthropology; bepress|Social and Behavioral Sciences|Anthropology|Social and Cultural Anthropology; evolution of religion; 03 medical and health sciences; Big Gods; bepress|Social and Behavioral Sciences; moralizing supernatural punishment; SocArXiv|Social and Behavioral Sciences; SocArXiv|Social and Behavioral Sciences|Anthropology|Social and Cultural Anthropology

The causes, consequences, and timing of the rise moralizing religions in world history have been focus intense debate. Progress has limited by availability quantitative data to test competing theories, divergent ideas regarding both predictor outcomes variables, differences opinion over methodology. To address all these problems, we utilize Seshat: Global History Databank, a large storehouse information designed theories concerning evolutionary drivers social complexity. In addition Big Gods hypothesis, which proposes that religion contributed success increasingly large-scale complex societies, consider role warfare, animal husbandry, agricultural productivity religions. Using broad range new measures belief supernatural punishment, find strong support for previous research showing such beliefs did not drive By contrast, our analyses indicate intergroup supported resource availability, played major evolution complexity Thus, correlation between seems result from shared drivers, rather than direct causal relationships two variables.