Abstract

The origins of religion and of complex societies represent evolutionary puzzles1,2,3,4,5,6,7,8. The ‘moralizing gods’ hypothesis offers a solution to both puzzles by proposing that belief in morally concerned supernatural agents culturally evolved to facilitate cooperation among strangers in large-scale societies9,10,11,12,13. Although previous research has suggested an association between the presence of moralizing gods and social complexity3,6,7,9,10,11,12,13,14,15,16,17,18, the relationship between the two is disputed9,10,11,12,13,19,20,21,22,23,24, and attempts to establish causality have been hampered by limitations in the availability of detailed global longitudinal data. To overcome these limitations, here we systematically coded records from 414 societies that span the past 10,000 years from 30 regions around the world, using 51 measures of social complexity and 4 measures of supernatural enforcement of morality. Our analyses not only confirm the association between moralizing gods and social complexity, but also reveal that moralizing gods follow—rather than precede—large increases in social complexity. Contrary to previous predictions9,12,16,18, powerful moralizing ‘big gods’ and prosocial supernatural punishment tend to appear only after the emergence of ‘megasocieties’ with populations of more than around one million people. Moralizing gods are not a prerequisite for the evolution of social complexity, but they may help to sustain and expand complex multi-ethnic empires after they have become established. By contrast, rituals that facilitate the standardization of religious traditions across large populations25,26 generally precede the appearance of moralizing gods. This suggests that ritual practices were more important than the particular content of religious belief to the initial rise of social complexity.

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Data availability

The full machine-readable dataset is available as Supplementary Data 1, and at http://seshatdatabank.info/datasets. Full coding data with detailed explanations and references are available at http://seshatdatabank.info/data, and are summarized in Supplementary Table 2. The data include the coded levels of uncertainty and disagreement, the textual explanations and the references for each of the variables for all polities used in our analysis. These webpages also make it possible to comment on each of our data points and suggest additions or corrections and thus provide an up-to-date and dynamic dataset that undergoes continual improvement by members of the Seshat team and external scholars. To maximize transparency, we have tied each cluster of variables to the names of the research assistants who gathered the data, and to the names of the experts who reviewed the data.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Darwin, C. The Descent of Man, and Selection in Relation to Sex (John Murray, London, 1871).

  2. 2.

    Bellah, R. N. Religion in Human Evolution: From the Paleolithic to the Axial Age (Harvard Univ. Press, Cambridge, 2011).

  3. 3.

    Purzycki, B. G. et al. Moralistic gods, supernatural punishment and the expansion of human sociality. Nature 530, 327–330 (2016).

  4. 4.

    Watts, J., Sheehan, O., Atkinson, Q. D., Bulbulia, J. & Gray, R. D. Ritual human sacrifice promoted and sustained the evolution of stratified societies. Nature 532, 228–231 (2016).

  5. 5.

    Currie, T. E., Greenhill, S. J., Gray, R. D., Hasegawa, T. & Mace, R. Rise and fall of political complexity in island South-East Asia and the Pacific. Nature 467, 801–804 (2010).

  6. 6.

    Henrich, J. et al. Markets, religion, community size, and the evolution of fairness and punishment. Science 327, 1480–1484 (2010).

  7. 7.

    Botero, C. A. et al. The ecology of religious beliefs. Proc. Natl Acad. Sci. USA 111, 16784–16789 (2014).

  8. 8.

    Turchin, P. et al. Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization. Proc. Natl Acad. Sci. USA 115, E144–E151 (2018).

  9. 9.

    Norenzayan, A. et al. The cultural evolution of prosocial religions. Behav. Brain Sci. 39, e1 (2016).

  10. 10.

    Norenzayan, A. Big questions about big gods: response and discussion. Religion Brain Behav. 5, 327–342 (2015).

  11. 11.

    Johnson, D. D. P. God’s punishment and public goods: a test of the supernatural punishment hypothesis in 186 world cultures. Hum. Nat. 16, 410–446 (2005).

  12. 12.

    Johnson, D. D. P. The wrath of the academics: criticisms, applications, and extensions of the supernatural punishment hypothesis. Religion Brain Behav. 8, 320–350 (2018).

  13. 13.

    Schloss, J. P. & Murray, M. J. Evolutionary accounts of belief in supernatural punishment: a critical review. Religion Brain Behav. 1, 46–99 (2011).

  14. 14.

    Roes, F. L. & Raymond, M. Belief in moralizing gods. Evol. Hum. Behav. 24, 126–135 (2003).

  15. 15.

    Peoples, H. C. & Marlowe, F. W. Subsistence and the evolution of religion. Hum. Nat. 23, 253–269 (2012).

  16. 16.

    Watts, J. et al. Broad supernatural punishment but not moralizing high gods precede the evolution of political complexity in Austronesia. Proc. R. Soc. B 282, 20142556 (2015).

  17. 17.

    Gray, R. D. & Watts, J. Cultural macroevolution matters. Proc. Natl Acad. Sci. USA 114, 7846–7852 (2017).

  18. 18.

    Raffield, B., Price, N. & Collard, M. Religious belief and cooperation: a view from Viking-age Scandinavia. Religion Brain Behav. 9, 2–22 (2019).

  19. 19.

    Baumard, N. & Boyer, P. Explaining moral religions. Trends Cogn. Sci. 17, 272–280 (2013).

  20. 20.

    Baumard, N., Hyafil, A., Morris, I. & Boyer, P. Increased affluence explains the emergence of ascetic wisdoms and moralizing religions. Curr. Biol. 25, 10–15 (2015).

  21. 21.

    Mullins, D. A. et al. A systematic assessment of ‘Axial Age’ proposals using global comparative historical evidence. Am. Sociol. Rev. 83, 596–626 (2018).

  22. 22.

    Purzycki, B. G. et al. Material security, life history, and moralistic religions: a cross-cultural examination. PLoS ONE 13, e0193856 (2018).

  23. 23.

    Stausberg, M. Big gods in review: introducing Ara Norenzayan and his critics. Religion 44, 592–608 (2014).

  24. 24.

    McKay, R. & Whitehouse, H. Religion and morality. Psychol. Bull. 141, 447–473 (2015).

  25. 25.

    Whitehouse, H. Modes of Religiosity: A Cognitive Theory of Religious Transmission (AltaMira, Walnut Creek, 2004).

  26. 26.

    Whitehouse, H., François, P. & Turchin, P. The role of ritual in the evolution of social complexity: five predictions and a drum roll. Cliodynamics 6, 199–216 (2015).

  27. 27.

    Norenzayan, A. & Shariff, A. F. The origin and evolution of religious prosociality. Science 322, 58–62 (2008).

  28. 28.

    Shariff, A. F., Willard, A. K., Andersen, T. & Norenzayan, A. Religious priming: a meta-analysis with a focus on prosociality. Pers. Soc. Psychol. Rev. 20, 27–48 (2016).

  29. 29.

    Turchin, P. et al. Seshat: The Global History Databank. Cliodynamics 6, 77–107 (2015).

  30. 30.

    Murdock, G. P. Ethnographic atlas: a summary. Ethnology 6, 109–236 (1967).

  31. 31.

    Swanson, G. E. The Birth of the Gods: The Origin of Primitive Beliefs (Michigan Univ. Press, Ann Arbor, 1960).

  32. 32.

    Divale, W. Pre-Coded Variables for the Standard Cross-Cultural Sample Vols 1 and 2 (York College, New York, 2000).

  33. 33.

    Johnson, D. God is Watching You: How the Fear of God Makes Us Human (Oxford Univ. Press, New York, 2016).

  34. 34.

    Norenzayan, A. Big Gods: How Religion Transformed Cooperation and Conflict (Princeton Univ. Press, Princeton, 2013).

  35. 35.

    Haidt, J. & Graham, J. When morality opposes justice: conservatives have moral intuitions that liberals may not recognize. Soc. Justice Res. 20, 98–116 (2007).

  36. 36.

    Curry, O. S. in The Evolution of Morality (eds Shackelford, T. K. & Hansen, R. D.) 27–51 (Springer, Cham, 2016).

  37. 37.

    Whitehouse, H. & Lanman, J. The ties that bind us: ritual, fusion, and identification. Curr. Anthropol. 55, 674–695 (2014).

  38. 38.

    Whitehouse, H. & Martin, L. H. Theorizing Religions Past: Archaeology, History, and Cognition (AltaMira, Blue Ridge Summit, 2004).

  39. 39.

    Atkinson, Q. D. & Whitehouse, H. The cultural morphospace of ritual form: examining modes of religiosity cross-culturally. Evol. Hum. Behav. 32, 50–62 (2011).

  40. 40.

    Slingerland, E. & Sullivan, B. Durkheim with data: the Database of Religious History. J. Am. Acad. Relig. 85, 312–347 (2017).

  41. 41.

    Wade, L. Birth of the moralizing gods. Science 349, 918–922 (2015).

  42. 42.

    R Core Team. R: A Language and Environment for Statistical Computing. https://www.r-project.org/ (2015).

  43. 43.

    Rubin, D. B. Multiple Imputation for Nonresponse in Surveys (Wiley, New York, 1987).

  44. 44.

    Udell, M., Horn, C., Zadeh, R. & Boyd, S. Generalized low rank models. Found. Trends Mach. Learn. 9, 1–118 (2016).

  45. 45.

    Stahlschmidt, S., Härdle, W. K. & Thome, H. An application of principal component analysis on multivariate time-stationary spatio-temporal data. Spat. Econ. Anal. 10, 160–180 (2015).

  46. 46.

    Hassani, H. Singular spectrum analysis: methodology and comparison. J. Data Sci. 5, 239–257 (2007).

  47. 47.

    Mace, R. & Pagel, M. The comparative method in anthropology. Curr. Anthropol. 35, 549–564 (1994).

  48. 48.

    Turchin, P. Fitting dynamical regression models to Seshat data. Cliodynamics 9, 25–58 (2018).

  49. 49.

    Granger, C. W. J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424–438 (1969).

  50. 50.

    Kleinberg, S. Causality, Probability, and Time (Cambridge Univ. Press, Cambridge, 2013).

  51. 51.

    Eff, E. A. & Dow, M. M. How to deal with missing data and Galton’s problem in cross-cultural survey research: a primer for R. Struct. Dyn. 3, 1–29 (2009).

  52. 52.

    Eff, E. A. & Routon, P. W. Farming and fighting: an empirical analysis of the ecological-evolutionary theory of the incidence of warfare. Struct. Dyn. 5, 1–33 (2012).

  53. 53.

    Hammarström, H., Forkel, R., Haspelmath, M. & Nordhoff, S. Glottolog version 2.3 http://glottolog.org (2014).

  54. 54.

    Dryer, M. S. & Haspelmath, M. The World Atlas of Language Structures online http://wals.info (Max Planck Institute for Evolutionary Anthropology, 2013).

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Acknowledgements

We thank Q. Atkinson and A. Willard for feedback on an earlier version of the manuscript and E. Postma for discussions on parts of the statistical analyses. We acknowledge the contributions of our team of research assistants, post-doctoral researchers, consultants and experts. See http://www.seshatdatabank.info for a comprehensive list of private donors, partners, experts and consultants. This work was supported by an ESRC Large Grant entitled ‘Ritual, Community, and Conflict’ (REF RES-060-25-0085), a John Templeton Foundation grant to the Evolution Institute entitled ‘Axial-Age Religions and the Z-Curve of Human Egalitarianism’, a Tricoastal Foundation grant to the Evolution Institute entitled ‘The Deep Roots of the Modern World: The Cultural Evolution of Economic Growth and Political Stability’, an Advanced Grant (‘Ritual Modes: Divergent modes of ritual, social cohesion, prosociality, and conflict’, grant agreement no. 694986) and a Starter Grant (‘The Cultural Evolution & Ecology of Institutions’, grant agreement no. 716212) from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme, an award from the Templeton World Charity Foundation entitled ‘Cognitive and Cultural Foundations of Religion and Morality’ (TWCF0164), a Keio Research Institute at SFC Startup Grant, a Keio Gijuku Academic Development Fund Individual Grant and a grant from the European Union Horizon 2020 Research and Innovation Programme (grant agreement no. 644055 (ALIGNED, www.aligned-project.eu)).

Reviewer information

Nature thanks Carol Ember, Peter J. Richerson and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

  1. These authors contributed equally: Harvey Whitehouse, Pieter François, Patrick E. Savage

Affiliations

  1. Centre for the Study of Social Cohesion, University of Oxford, Oxford, UK

    • Harvey Whitehouse
    • , Pieter François
    • , Patrick E. Savage
    •  & Robert M. Ross
  2. St Benet’s Hall, Oxford, UK

    • Pieter François
  3. Faculty of Environment and Information Studies, Keio University, Fujisawa, Japan

    • Patrick E. Savage
  4. Human Behaviour & Cultural Evolution Group, Department of Biosciences, University of Exeter, Penryn, UK

    • Thomas E. Currie
  5. School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland

    • Kevin C. Feeney
  6. Seshat: Global History Databank, Evolution Institute, San Antonio, FL, USA

    • Enrico Cioni
    •  & Rosalind Purcell
  7. ARC Centre of Excellence in Cognition and its Disorders and Department of Psychology, Royal Holloway, University of London, Egham, UK

    • Robert M. Ross
  8. Department of Anthropology and Archaeology, University of Bristol, Bristol, UK

    • Robert M. Ross
  9. Department of Modern & Classical Language Studies, Kent State University, Kent, OH, USA

    • Jennifer Larson
  10. Faculty of Oriental Studies, University of Oxford, Oxford, UK

    • John Baines
  11. Department of Chinese Language and Culture, Asia-Africa-Institute, University of Hamburg, Hamburg, Germany

    • Barend ter Haar
  12. Department of Anthropology, University of Texas at Austin, Austin, TX, USA

    • Alan Covey
  13. Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA

    • Peter Turchin
  14. Complexity Science Hub Vienna, Wien, Austria

    • Peter Turchin

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Contributions

H.W., P.F. and P.E.S. designed the study, with input from P.T., T.E.C., K.C.F. and R.M.R.; E.C. and R.P. coded the religion and ritual data, with additional input from J.L., J.B., B.t.H and A.C.; P.E.S. analysed the data, with input from H.W., P.F., P.T., T.E.C. and R.M.R.; P.E.S., H.W. and P.F. drafted the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Patrick E. Savage.

Extended data figures and tables

  1. Extended Data Fig. 1 Social complexity time series for individual regions.

    The 12 regions for which social complexity data are available both before and after the appearance of moralizing gods are shown. Vertical bands represent the period in which the first evidence of moralizing gods (red) and doctrinal rituals (blue) appeared. Grey shading represents 95% confidence intervals based on a PCA using multiple imputation8. Source data

  2. Extended Data Fig. 2 Full time series showing mean social complexity over time before and after the appearance of moralizing gods.

    n = 12 regions with data before and after the appearance of moralizing gods. Social complexity has been scaled so that the society with the highest social complexity (Qing Dynasty, China, around ad 1900) has a value of 1 and the society with the lowest social complexity (Early Woodland, Illinois, USA, around 400 bc) has a value of 0. Vertical bands represent the period in which moralizing gods and doctrinal rituals first appeared. All errors represent 95% confidence intervals, with the exception of the vertical bar for moralizing gods, which represents the mean duration of the polity in which moralizing gods appeared (because times are normalized to the time of first evidence of moralizing gods, and there is thus no variance in this parameter). Lack of confidence intervals indicates data from only a single region. This figure is identical to Fig. 2a, except that it also includes all available data before and after moralizing gods, rather than being restricted to a window of 2,000 years before and after. Source data

  3. Extended Data Fig. 3 Social complexity before and after the appearance of MHG.

    This is a version of Fig. 2 in which analyses are restricted to only MHG, rather than the broader definition of moralizing gods used in Fig. 2 and elsewhere (which includes BSP as well as MHG). a, Time series showing the mean social complexity over time for 2,000 years before and after the appearance of MHG. n = 10 regions with social complexity data for before and after moralizing high gods. Social complexity has been scaled so that the society with the highest social complexity (Qing Dynasty, China, around ad 1900) has a value of 1 and the society with the lowest social complexity (Early Woodland, Illinois, USA, around 400 bc) has a value of 0. Vertical bands represent the period in which MHG and doctrinal rituals first appeared. All errors represent 95% confidence intervals, with the exception of the vertical bar for MHG, which represents the mean duration of the polity in which MHG appeared (because times are normalized to the time of first evidence of MHG and there is therefore no variance in this parameter). b, Histogram of differences in rates of change in social complexity after minus before the appearance of MHG (n = 158 time windows from the 10 regions). The y axis represents the number of time windows out of 158. Source data

  4. Extended Data Table 1 Timing and rates of change in social complexity before and after the earliest precolonial evidence of moralizing gods
  5. Extended Data Table 2 Logistic regression results predicting moralizing gods
  6. Extended Data Table 3 Analyses with doctrinal rituals instead of moralizing gods as the dependent variable
  7. Extended Data Table 4 Robustness analyses modifying modelling assumptions of the analyses
  8. Extended Data Table 5 List of the 51 social complexity variables analysed

Supplementary information

  1. Supplementary Information

    This file contains Supplementary Material, including Supplementary Tables S1-S18.

  2. Reporting Summary

  3. Supplementary Data

    This file contains the raw dataset containing all data analysed in the paper.

Source data

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