Opponents of the new mechanistic account of scientific explanation argue that the new mechanists are committed to a ‘More Details Are Better’ claim: adding details about the mechanism always improves an explanation. Due to this commitment, the mechanistic account cannot be descriptively adequate as actual scientific explanations usually leave out details about the mechanism. In reply to this objection, defenders of the new mechanistic account have highlighted that only adding relevant mechanistic details improves an explanation and that relevance is to be determined relative to the phenomenon-to-be-explained. Craver and Kaplan (B J Philos Sci 71:287–319, 2020) provide a thorough reply along these lines specifying that the phenomena at issue are contrasts. In this paper, we will discuss Craver and Kaplan’s reply. We will argue that it needs to be modified in order to avoid three problems, i.e., what we will call the Odd Ontology Problem, the Multiplication of Mechanisms Problem, and the Ontic Completeness Problem. However, even this modification is confronted with two challenges: First, it remains unclear how explanatory relevance is to be determined for contrastive explananda within the mechanistic framework. Second, it remains to be shown as to how the new mechanistic account can avoid what we will call the ‘Vertical More Details are Better’ objection. We will provide answers to both challenges.
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Craver and Kaplan use the label ‘MDB_r’ (with an index). For our purposes, it is more convenient to use the label ‘MRDB’.
Note that the mutual manipulability account is not a description about what should be a component of a mechanism for a given phenomenon but rather a recipe for determining what is a component of a mechanism for a given phenomenon.
‘dogged’ → ‘fdogged’ → ‘frogged’ → ‘froggyd’ → ‘froggy’
This criterion is equivalent to the one on p. 21 above. The edit distance from M to M* is 0 iff M and M* have the same constituents.
Note that the question we are interested in differs from the question that Woodward answers with his account of conditional irrelevance. Our question is ‘When is an explanation improved by going down the mechanistic hierarchy?’ Woodward’s question is ‘When is a higher-level explanation better than or as good as a fundamental level explanation?’ Woodward’s perspective differs from ours in the sense that in his context it is commonly assumed that (i) there are different explanations at different levels (whereas we assume that there is one explanation that can extend over multiple levels), and (ii) that lowest-level explanations are by default the preferred ones (due to considerations of causal closure and exclusion). Based on these considerations, the question arises whether higher-level explanations can at least sometimes be better or at least as good as lowest-level explanations. Here, Woodward provides a convincing answer: a given higher-level explanation is at least as good as the lowest-level explanation if the lowest-level explanation is irrelevant for the explanandum conditional on the higher-level explanation. In the mechanistic picture, however, explanation is a top-down matter: while the first lower-level is clearly explanatorily relevant for the phenomenon (say, the activity of the hippocampus is clearly explanatorily relevant for spatial memory), the lowest level is clearly not (say, the interactions between quarks is clearly irrelevant for the explanation of spatial memory). The question, then, is where in the mechanistic hierarchy explanatory relevance stops.
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Kohár, M., Krickel, B. (2021). Compare and Contrast: How to Assess the Completeness of Mechanistic Explanation. In: Calzavarini, F., Viola, M. (eds) Neural Mechanisms. Studies in Brain and Mind, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-030-54092-0_17
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