Abstract
How can we understand the results of a simulation study? In this article, I address this epistemic question for social science simulations. I argue that we can distinguish two categories of simulations: simulations STE, which possess key features that resemble the epistemology and methodology of thought experiments, and simulations SE, which resemble the epistemology and methodology of experiments. Based on Woodward’s theory of causal explanation, I put forward the hypothesis that STE provide more understanding and a different kind of knowledge than SE because they give well-founded answers to what-if-things-had-been-different questions. Epistemic opacity is a persistent problem for simulations SE, while for STE it need not necessarily be so.
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Notes
- 1.
In this article, I avoid the term social simulation for the reason that this umbrella term also encompasses models employed by, for example, ecologists and computer scientists, who do not relate their work to social theory. Instead, I use the term social science simulation to indicate this difference.
- 2.
Hartmann’s definition applies to non-computational simulations as well. However, they are not relevant for the argument presented here.
- 3.
It is not certain that the restrictive definition of “simulation” by Hartmann (1996) still applies to all examples of current computer simulation, even in the particular domain of social sciences: e.g., there have been simulations that do not imitate a phenomenon with a temporal dimension (see e.g. Winsberg 2009). From this viewpoint, the exclusion of Monte Carlo simulations may also seem excessive and unjustified. However, for our present purposes we prefer a restrictive definition for two reasons: First, the vast majority of simulations in the social sciences are included in this restrictive definition, and it is more transparent to develop the present argument in line with this restrictive definition. Second, the argument may be transferred later to a more comprehensive definition of simulation, including, e.g., Monte Carlo simulations. Consideration of further sorts of current computer simulation would exceed the space limitations of a journal article.
- 4.
I remain neutral toward two theses that have established an argument view. I do not argue that each thought experiment can be reconstructed as an argument (Norton’s thesis put forward in Norton 1996), nor do I argue that each computer simulation can be reconstructed as an argument (Beisbart’s thesis put forward in Beisbart 2012).
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The author would like to thank Andreas Kaminski for his valuable comments.
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Saam, N.J. (2017). Understanding Social Science Simulations: Distinguishing Two Categories of Simulations. In: Resch, M., Kaminski, A., Gehring, P. (eds) The Science and Art of Simulation I . Springer, Cham. https://doi.org/10.1007/978-3-319-55762-5_6
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