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

This article is a response to Slingerland et al. who criticize the quality of the data from Seshat: Global History Databank utilized in our Nature paper entitled “Complex Societies Precede Moralizing Gods throughout World History”. Their critique centres around the roles played by research assistants and experts in procuring and curating data, periodization structure, and so-called “data pasting” and “data filling”. We show that these criticisms are based on misunderstandings or misrepresentations of the methods used by Seshat researchers. Overall, Slingerland et al.’s critique (which is crosslinked online here) does not call into question any of our main findings, but it does highlight various shortcomings of Slingerland et al.’s database project. Our collective efforts to code and quantify features of global history hold out the promise of a new era in the study of global history but only if critique can be conducted constructively in good faith and both the benefits and the pitfalls of open science fully recognized.