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Understanding Epistemological Debates in the Humanities and Social Sciences Can Aid in Model Development: Modeling Interpretive and Explanatory Theories

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Part of the book series: New Approaches to the Scientific Study of Religion ((NASR,volume 7))

Abstract

When embarking on a new model, a programmer working with scholars in the humanities is often tasked with helping a likely non-programmer(s) with critical decisions concerning how to set about modeling the theory at hand. I argue that, in these early stages of development, the goals of the researcher and epistemological considerations are of paramount importance to the development of valid computational models. In order to start this discussion with a real-world example, this chapter outlines a mistake, made by myself, in a critical stage early on in the modelling process. Specifically, using early discussions with the theorist, I suggested modeling the theory as an agent-based model. After some critical reflection after substantial development, I came to the conclusion that the theory is better modelled as a system dynamics model. In the chapter, I reflect on what drove me to make the original mistake, what caused me to realize the error, and what the result of correcting the error was. I share this mistake in this chapter for two reasons: (1) so that others in similar situations might not fall into the same trappings and (2) to open up a dialogue concerning epistemology of the social sciences and humanities insofar as it relates to modelling and simulation. My general conclusion is that the thinking received by the social scientist and humanities scholar should be fully flushed out at early stages of model development, as their strength is attention to theoretical nuance. This is of utmost importance to model development, which if unaddressed should still cause issues later during model validation and verification.

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Notes

  1. 1.

    This flattening of social heterogeneity so as to deal with social level variables being both explanans and explanandum is something addressed elsewhere as the “Durkheimian fallacy” (Lane 2013).

  2. 2.

    Even as distributions, it is unclear why it is that such a model should be interpreted as dealing with semantic content. Such an interpretation may be too far removed from the target of the model. This parallels a serious issue in the small field of modeling and simulation of cultural phenomenon where scientists use models from their own fields to try and “explain” some phenomenon in the social sciences without regard or consulting actual subject matter experts. Leading to such nonsense conclusions like we can explain human cooperation and alignment by understanding cooperative decision making as a public goods game based in thermodynamics as opposed to the psychology of human decision making (Adami et al. 2017).

References

  • Adami, C., N. Pasmanter, and A. Hintze. 2017. Thermodynamics of evolutionary games. ArXiv: 1–16.

    Google Scholar 

  • Balaban, M., P. Hester, and S.Y. Diallo. 2014. Towards a theory of multi-method M&S approach: Part 1. In Proceedings of the 2014 Winter simulation conference, ed. A. Tolk, S.Y. Diallo, L. Ryzhov, L. Yilmaz, S. Buckley, and J.A. Miller, 1652–1663. Savannah: IEEE Press.

    Chapter  Google Scholar 

  • Bechtel, W. 2009. Looking down, around, and up: Mechanistic explanation in psychology. Philosophical Psychology 22 (5): 543–564. https://doi.org/10.1080/09515080903238948.

    Article  Google Scholar 

  • Blondel, V.D., J.-L. Guillaume, R. Lambiotte, and E. Lefebvre. 2008. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 10008 (10): 6. https://doi.org/10.1088/1742-5468/2008/10/P10008.

    Article  Google Scholar 

  • Bunge, M. 1998. Social science under debate: A philosophical perspective. Toronto: University of Toronto Press.

    Book  Google Scholar 

  • ———. 2011. Knowledge: Genuine and Bogus. Science and Education 20 (5–6): 411–438. https://doi.org/10.1007/s11191-009-9225-3.

    Article  Google Scholar 

  • Epstein, J.M. 1999. Agent-based computational models and generative social science. Complexity 4 (5): 41–60. https://doi.org/10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9> 3.3.CO;2-6.

    Article  Google Scholar 

  • ———. 2006. Agent-based computational models and generative social science. In Generative social science, ed. J.M. Epstein, 1–43. Princeton/Oxford: Princeton University Press. https://doi.org/10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9>3.0.CO;2-F.

    Chapter  Google Scholar 

  • Gilbert, N. 2008. The idea of agent-based modeling. In Agent-based models, 2–21. Thousand Oaks: SAGE.

    Chapter  Google Scholar 

  • Grimm, V., U. Berger, D.L. DeAngelis, J.G. Polhill, J. Giske, and S.F. Railsback. 2010. The ODD protocol: A review and first update. Ecological Modelling 221 (23): 2760–2768. https://doi.org/10.1016/j.ecolmodel.2010.08.019.

    Article  Google Scholar 

  • Lakatos, I. 1978. The methodology of scientific research programmes: Volume 1: Philosophical papers, ed. J. Worall and G. Currie. Cambridge: Cambridge University Press.

    Google Scholar 

  • Lane, J.E. 2013. Method, theory, and multi-agent artificial intelligence: Creating computer models of complex social interaction. Journal for the Cognitive Science of Religion 1 (2): 161–180.

    Article  Google Scholar 

  • ———. 2017. Can we predict religious extremism? Religion. Brain & Behavior 7 (4): 299–304. https://doi.org/10.1080/2153599X.2016.1249923.

    Article  Google Scholar 

  • ———. 2018a. Bridging qualitative and quantitative approaches to religion, 26–32. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2018.1429008.

    Article  Google Scholar 

  • ———. 2018b. The emergence of social schemas and lossy conceptual information networks: How information transmission can lead to the apparent “emergence” of culture. In Emergent behavior in complex systems engineering: A modeling and simulation approach, ed. S. Mittal, S.Y. Diallo, and A. Tolk, 1st ed., 329–256. New York: Wiley.

    Google Scholar 

  • Lior, Y. 2015. Kabbalah and neo-confucianism: A comparitive morphology of medieval moments. Boston University.

    Google Scholar 

  • Lynch, C.J. 2015. A taxonomy for classifying terminologies that describe simulations with multiple models. In Proceedings of the 2015 Winter simulation conference, ed. L. Yilmaz, W.K.V. Chan, I. Moon, M.K. Roeder, C. Macal, M.D. Rossetti, et al., 1621–1632. Huntington Beach: IEEE Computer Society.

    Chapter  Google Scholar 

  • Lynch, C., J.J. Padilla, S.Y. Diallo, J. Sokolowski, and C. Banks. 2014. A multi-paradigm modeling framework for modeling and simulating problem situations. In Proceedings of the 2014 Winter simulation conference, ed. A. Tolk, S.Y. Diallo, L. Ryzhov, L. Yilmaz, S. Buckley, and J.A. Miller, 1688–1699. Savannah: IEEE Press.

    Chapter  Google Scholar 

  • Robinson, S., R. Brooks, K. Kotiadis, and D.-J. van der Zee, eds. 2011. Conceptual modeling for discrete-event simulation. Boca Raton: Taylor & Francis Group.

    Google Scholar 

  • Sokal, A.D. 2010. Beyond the Hoax: Science, philosophy and culture. Oxford: Oxford University Press.

    Google Scholar 

  • Sperber, D. 1985. Anthropology and psychology: Towards and epidemiology of representations. Man 20 (1): 73–89. Retrieved from http://www.jstor.org/stable/2802222.

    Article  Google Scholar 

  • Sterman, J.D. 2000. Business dynamics: Systems thinking and modeling for a complex world. Boston: Irwin McGraw-Hill.

    Google Scholar 

  • The AnyLogic Company. 2017. AnyLogic 8.2.3. St. Petersburg: The AnyLogic Company. Retrieved from www.anylogic.com.

    Google Scholar 

  • Tolk, A., S.Y. Diallo, J.J. Padilla, and H. Herencia-Zapana. 2013. Reference modelling in support of M&S-foundations and applications. Journal of Simulation 7 (2): 69–82. https://doi.org/10.1057/jos.2013.3.

    Article  Google Scholar 

  • Vangheluwe, H., J. De Lara, and P.J. Mosterman. 2000. An introduction to multiparadigm modelling and simulation. Ais2002: 9–20. Retrieved from https://msdl.cs.mcgill.ca/people/hv/teaching/MSBDesign/COMP762B2003/resources/AIS.paper.pdf.

  • Viana, J., S.C. Brailsford, V. Harindra, and P.R. Harper. 2014. Combining discrete-event simulation and system dynamics in a healthcare setting: A composite model for Chlamydia infection. European Journal of Operational Research 237 (1): 196–206. https://doi.org/10.1016/j.ejor.2014.02.052.

    Article  Google Scholar 

  • Wilensky, U. 2005. NetLogo Wolf Sheep predation (Docked Hybrid) model. Evanston: Center for Connected Learning and Computer-Based Modeling, Northwestern University.

    Google Scholar 

  • Wilensky, U., and K. Reisman. 2006. Thinking like a Wolf, a Sheep, or a Firefly: Learning biology through constructing and testing computational theories – An embodied modeling approach. Cognition and Instruction 24 (2): 171–209. https://doi.org/10.1207/s1532690xci2402.

    Article  Google Scholar 

  • Xygalatas, D. 2012. The Burning Saints: Cognition and culture in the fire-walking rituals of the Anastenaria. Bristol: Equinox Publishing Ltd.

    Google Scholar 

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Correspondence to Justin E. Lane .

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Lane, J.E. (2019). Understanding Epistemological Debates in the Humanities and Social Sciences Can Aid in Model Development: Modeling Interpretive and Explanatory Theories. In: Diallo, S., Wildman, W., Shults, F., Tolk, A. (eds) Human Simulation: Perspectives, Insights, and Applications. New Approaches to the Scientific Study of Religion , vol 7. Springer, Cham. https://doi.org/10.1007/978-3-030-17090-5_4

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