Abstract
Explanatory realism is the view that explanations work by providing information about relations of productive determination such as causation or grounding. The view has gained considerable popularity in the last decades, especially in the context of metaphysical debates about non-causal explanation. What makes the view particularly attractive is that it fits nicely with the idea that not all explanations are causal whilst avoiding an implausible pluralism about explanation. Another attractive feature of the view is that it allows explanation to be a partially epistemic, context-dependent phenomenon. In spite of its attractiveness, explanatory realism has recently been subject to criticism. In particular, Taylor (Philos Stud 175(1):197–219, 2018). has presented four types of explanation that the view allegedly cannot account for. This paper defends explanatory realism against Taylor’s challenges. We will show that Taylor’s counterexamples are either explanations that turn out to provide information about entities standing in productive determination relations or that they are not genuine explanations in the first place.
Highlights
Explanatory realism is the view that all explanations provide information about relations of productive determination such as, inter alia, causation and grounding
At one point Taylor seems to suggest that the aims of providing understanding via analogies goes against the spirit of explanatory realism: One could argue that whatever is going on in these cases it is not explanation, because the primary goal is to help another person to understand some phenomenon, rather than to give information about whatever metaphysically determines that phenomenon. (Taylor 2018, pp. 205–206)
Theories of explanation that take into account the use of statistical rules frequently incorporate the assumption that, in explanatory cases, such rules are a guide to causal facts—which is in line with explanatory realism.34 (Theories that take mere statistical relevance as sufficient for explanatory relevance are widely dismissed.35) This, I take it, is why Kahnemann dismisses the purported explanation of the relation between population density and cancer incidence in terms of the Law of Small Numbers
Summary
Explanatory realism is the view that all explanations provide information about relations of productive determination such as, inter alia, causation and grounding. Taylor (2018) has recently presented four types of explanations that the view allegedly cannot account for: analogical explanations, explanations by rules, explanations by reductio ad absurdum, and certain statistical explanations Such explanations, she argues, are well established in scientific practice but do not provide information about productive determination relations. Engaging with Taylor’s arguments is valuable as they pinpoint several features of explanatory realism that are often not spelled out in sufficient detail This pertains, in particular, to the sense in which explanations are about entities standing in determination relations. I exclude the category of statistical explanation as these cases—as Taylor admits herself—do not pose straightforward counterexamples to realism but rather prompt further developments in the theory of probabilistic causation or probabilistic grounding.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callSimilar Papers
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
