A Regularist Approach to Mechanistic Type-Level Explanation

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Abstract
Most defenders of the new mechanistic approach accept ontic constraints for successful scientific explanation (Illari 2013; Craver 2014). The minimal claim is that scientific explanations have objective truthmakers, namely mechanisms that exist in the physical world independently of any observer and that cause or constitute the phenomena-to- be-explained. How can this idea be applied to type-level explanations? Many authors at least implicitly assume that in order for mechanisms to be the truthmakers of type-level explanation they need to be regular (Andersen 2012; Sheredos 2015). One problem of this assumption is that most mechanisms are (highly) stochastic in the sense that they “fail more often than they succeed” (Bogen 2005; Andersen 2012). How can a mechanism type whose instances are more likely not to produce an instance of a particular phenomenon type be the truthmaker of the explanation of that particular phenomenon type? In this paper, I will give an answer to this question. I will analyze the notion of regularity and I will discuss Andersen's suggestion for how to cope with stochastic mechanisms. I will argue that her suggestion cannot account for all kinds of stochastic mechanisms and does not provide an answer as to why regularity grounds type-level explanation. According to my analysis, a mechanistic type- level explanation is true if and only if at least one of the following two conditions is satisfied: the mechanism brings about the phenomenon more often than any other phenomenon (comparative regularity) or the phenomenon is more often brought about by the mechanism than by any other mechanism/causal sequence (comparative reverse regularity).
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2017, 2018
PhilPapers/Archive ID
KRIARA-2
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First archival date: 2016-05-02
Latest version: 3 (2017-07-20)
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References found in this work BETA
Explaining the Brain.Craver, Carl F.
Thinking About Mechanisms.Machamer, Peter K.; Darden, Lindley & Craver, Carl F.

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Citations of this work BETA
Intervening Into Mechanisms: Prospects and Challenges.Kästner, Lena & Andersen, Lise Marie

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2016-05-02

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