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An Inferential Account of Model Explanation

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Abstract

This essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step involving making counterfactual statements about the model itself and the second step involving making hypothetical statements transferring over claims derived from the model onto the target. To illustrate how this two-step activity proceeds, an agent-based simulation model is discussed.

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Notes

  1. Early versions of model-based approaches can be found in McMullin (1978, 1984, 1985).

  2. Notice that some of these views are said to be non-representational because they totally dismiss the relevance of any representational relationship between the model and the target in scientific modeling. On the other hand, my account to be developed in what follows seems to be representational because it proposes that a model represents a target in virtue of some activities performed by the modeler involved. So, it appears that my account conflicts with these non-representational views. However, I think the conflict is only superficial. First, as will become clear, the term ‘representation’ employed in my account should be deflationarily construed. Second, my account shares with these non-representational views the core idea that it is not any substantive representational relationship between the model and the target that makes the model able to do the work it is supposed to do in scientific modeling, e.g., model explanation.

  3. For a discussion of the isomorphism view, see Sneed (1971), Stegmüller (1976), Suppe (1977), Suppes (1962, 1967), Van Fraassen (1970, 1972); the partial isomorphism view, see Bueno (1997), Bueno et al. (2002, 2012), Da Costa and French (2003), French (1997, 2003), French and Ladyman (1998); and the similarity view, see Giere (1988), Godfrey-Smith (2006), Weisberg (2013).

  4. I think the Deductive-Nomological account is implausible because, first, its requirement for laws cannot be met in model explanation—many models do not invoke laws to explain, and second, many model explanations do not work in a deductive way but involving empirically finding explanatory (causal) variables.

  5. Christopher Pincock proposes a similar idea (“objective dependence relations”) when discussing non-causal explanations. According to him, in addition to causal dependence relations there are abstract dependence relations that can also be used to do explanatory work (Pincock 2015, 878).

  6. I thank Arnaud Pocheville and Pierrick Bourrat for alerting me to know that the inference from the model to its target (and vice versa) is in fact a hypothesis: because the model behaves in such-and-such a way we hypothesize that the target would also behave in such-and-such a way. The formation of the HS is indebted to many colleagues, including Arnaud Pocheville, Pierrick Bourra, Paul Griffiths, and Brian Hedden.

  7. “Agent-based modelling (ABM) is a computational modelling paradigm that enables us to describe how any agent will behave” (Wilensky and Rand 2015, 22). By the word agent, “we mean an autonomous individual element of a computer simulation. These individual elements have properties, states, and behaviors” (Ibid., 22).

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Acknowledgements

I am grateful to a number of friends and colleagues for feedback on early drafts of this work, including Pierrick Bourrat, Brett Calcott, Paul Griffiths, Patrick McGivern, Wendy Parker, Arnaud Pocheville, and Jan Sprenger. Special thanks is due to Paul Griffiths and Arnaud Pocheville, who gave me extremely useful help and encouragement over the course of developing this work. Thanks to an anonymous referee for his or her helpful suggestions. Thanks to the National Social Science Fund of China (grant number: 14ZDB018). Also thanks to the Minority and Philosophy committee in the University of Sydney Philosophy Department where I got useful language help.

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    Wei Fang

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Fang, W. An Inferential Account of Model Explanation. Philosophia 47, 99–116 (2019). https://doi.org/10.1007/s11406-018-9958-9

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