Abstract
This chapter critiques the new mechanistic explanatory program on grounds that, even when applied to the kinds of examples that it was originally designed to treat, it does not distinguish correct explanations from those that blunder. First, I offer a systematization of the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: they must (1) represent causal relations, (2) describe the proper parts, and (3) depict the system at the right “level.” Second, I argue that even the most developed attempts to fulfill these desiderata fall short by failing to appropriately constrain explanatorily apt mechanistic models.
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Notes
- 1.
Beyond token capacities and events, mechanists also aspire to treat regularities. Though the details are rarely made explicit, a given regularity can be explained via a mechanistic model jointly applicable to all of the particular systems underpinning a regularity’s instances; to do this, such a model must be at least somewhat abstract. For a discussion of how this might work, see Strevens’ “First Fundamental Theorem of Explanation” (2008: Chap. 7).
- 2.
Mechanists also judge unexplanatory phenomenological models—those that don’t purport to describe the inner workings of the system at issue—as well as mechanistic models that are false (even allowing for limited idealization) of the systems they purport to describe. As these exclusions will be uncontroversial for any fan of causal explanation, they require no discussion.
- 3.
Though this phenomenon is often modeled probabilistically, I treat it deterministically for the sake of expository simplicity. This simplification is innocent; over-permissiveness would be found equally on any probabilistic formulation.
- 4.
All four candidate models maintain that a neuron behaves thus because it is constituted in such a way that (1) it does not release neurotransmitters absent neurotransmitter exposure, and (2) exposure initiates a cascade of events, one of which is neurotransmitter release. Yet, the first condition is customarily taken for granted, and explanatory presentations focus on the second by describing the relevant features of the constitution of the neuron, and how exposure—given this constitution—has the specified result.
- 5.
Just as the overall phenomenon might be treated either probabilistically or deterministically, so it goes with this dynamic principle. Though I will not worry about the details, which sort of treatment is most apt will depend on how the channels are individuated. If single channels are separately represented, a probabilistic treatment is most appropriate; if large collections of channels are treated together, deterministic treatment will be preferred.
- 6.
Some might suggest that this model isn’t mechanistic at all, insisting that to be mechanistic a model must satisfy a causal constraint. This would be to cut up the project slightly differently than I have, but with no consequences for the overall argument. The task facing the new mechanist would still be to cash out the causal constraint; it matters not whether that constraint is appealed to in the definition of mechanistic models simpliciter, or (as in my exposition) in the characterization of explanatorily adequate mechanistic models.
- 7.
A zooming error is a species of carving error, and they are separated largely for rhetorical purposes. The first prototypically concerns using gerrymandered parts, while the second concerns otherwise “natural” parts at too fine (or coarse) a grain, considering the explanandum phenomenon.
- 8.
Though many peculiar sets will exist, not any will do: they must still be sufficiently expressive that they can be used, in concert with some set of dynamic principles, to bridge inputs and outputs.
- 9.
In particular, in addition to potentially addressing the carving problem, these conditions are offered as standards for distinguishing models that appeal to “real parts” from those that describe “fictional posits”(Craver 2007: 128–133).
- 10.
I focus on Craver’s presentation because it is the most systematic available, but it is characteristic of the new mechanist literature. For instance, compare Darden’s (2008: 961–962) discussion of “working entities” and Machamer et al.’s (2000: 5–6) comments on individuation of entities and activities.
- 11.
There are situations more complicated than this. If a mechanism contains a variety of redundant subsystems—each of which has a different range of stable functioning—the overall mechanism behavior could have a range of stability greater than that of any particular component, or component pathway. Yet, this possibility doesn’t undermine the more generic suggestion that some identifiable relationship exists between the stability of a mechanism’s parts’ properties and the mechanism’s systems-level behavior, and that this connection might be used to determine the relevant stability range required of mechanism parts.
- 12.
Craver sometimes presents the standard, quite reasonably, using his own symbolism. For instance, another version of (A) requires that “there is some change to X’s φ-ing that changes S’s ψ-ing” (2007b: 153). Though these alternative statements are compatible with the interpretation I give of the MM standard, and have informed my presentation, I do not use Craver’s notation because it would require too much space to adequately explain.
- 13.
Though this statement is from Craver’s (2007a), in explicating the view I am very influenced by Craver’s presentation in his (2007b). In correspondence, he reports that his presentation of the standard there is particularly careful.
- 14.
For a critique of the mechanists’ most promising response to the stop problem, that offered by difference-making accounts of causal explanation as articulated by Woodward (2003, 2010), and adopted explicitly by Craver (2007), see Franklin-Hall (2016). For my own positive proposal on the stop problem, see Franklin-Hall (forthcoming). A recent paper on this problem that came out too late for me to consider is Harbecke (2015).
- 15.
For a detailed account of the different things philosophers have meant by “level,” see Craver (2007, Chap. 5).
- 16.
As Lindley Darden explains in her overview of the movement, “[t]his work on mechanisms in biology originated (primarily) not as a response to past work in philosophy of science but from consideration of the work of biologists themselves, especially in molecular biology and neurobiology and biochemistry and cell biology” (2008: 958–959). Similarly, Bechtel writes that “these accounts of mechanistic explanation attempt to capture what biologists themselves provide when they offer explanations of such phenomena as digestion, cell division and protein synthesis” (2007: 270).
- 17.
There is one mildly ironic exception to my general diagnosis. The only putative black box that mechanists have opened is the scientists’ concept of “mechanism.” On reflection, this focus was imprudent. Not every concept used by scientists is meaty, and not every term reflects a genuine black box; “mechanism” is not a theoretical term within the science, but is a mere pointer, or placeholder—similar perhaps to the philosopher’s term “conception.”
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Franklin-Hall, L.R. (2016). New Mechanistic Explanation and the Need for Explanatory Constraints. In: Aizawa, K., Gillett, C. (eds) Scientific Composition and Metaphysical Ground. New Directions in the Philosophy of Science. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-56216-6_2
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