Abstract
Peirce provides various justifications of the knowledge enhancing role of abduction, even when abduction is not considered an inference to the best explanation in the classical sense of the expression, that is an inference necessarily characterized by an empirical evaluation phase, or inductive phase.
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- 1.
That is not inferences to the best explanation in the classical sense of the expression, involving an empirical evaluation phase.
- 2.
Poincaré says that these principles are “deduced” from experimental truths, but it is unlikely to think of them as fruit of deduction instead of abduction. I think that the use of the word deduction is just a way adopted by Poincaré to refer to a generic kind of scientific inference.
- 3.
Computer and AI scientists have suggested an interesting technique for negating hypotheses and accessing new ones: negation as failure (Clark 1978). I consider this kind of logical account of negation, studied by researchers into logic programming, to be very important also from the epistemological point of view. Negation as failure is active as a “rational” process of withdrawing previously-abduced hypotheses in everyday life, but also in certain subtle kinds of diagnostic (analytic interpretations in psychoanalysis—cf. Chap. 4, Sect. 4.2, this book) and other epistemological settings. Contrasted with classical negation, with the double negation of intuitionistic logic, and with the philosophical concept of Aufhebung (Toth 1991), negation as failure shows how a subject can decide to withdraw her hypotheses, while maintaining the “rationality” of her argumentations, in contexts where it is impossible to find contradictions or falsifications. Negation as failure in query evaluation process for a logical database is more extensively illustrated in (Magnani 2009, Chap. 2).
- 4.
Please keep in mind I am making an analogy between “not provable” and “not empirically fecund”.
- 5.
See Chap. 1, footnote 14.
- 6.
I have firstly introduced the problem of epistemological fictionalism in the previous chapter.
- 7.
In this last sense the capacity of scientific models to constitute new empirical domains and so new empirical knowability is ideally related to the emphasis that epistemology, in the last century, put on the theory-ladenness of scientific facts (Hanson, Popper, Lakatos, Kuhn): in this light, the formulation of observation statements presupposes significant knowledge, and the search for new observability in science is guided by scientific modeling.
- 8.
It has to be added that Suárez does not conflate scientific modeling with literary fictionalizing. He distinguishes scientific fictions from other kinds of fictions—the scientific ones are constrained by both the logic of inference and, in particular, the requirement to fit in with the empirical domain (Suárez 2009, 2010)—in the framework of an envisaged compatibility of “scientific fiction” with realism. This epistemological acknowledgment is not often present in other followers of fictionalism.
- 9.
I discussed the role of chance-seeking in scientific discovery in (Magnani 2007).
- 10.
Which, by the way, is the key topic of epistemology at least since Karl Popper and Thomas Kuhn.
- 11.
It is worth mentioning that the metaphor of “detonation” originated as a characterization of what happens when in an inconsistent theory ex falso is true. “Detonation” is also a catching play on the words of Russell’s famous 1905 paper “On denoting”, published in Mind. The phrase derives from Schotch and Jennings’ contribution to the paraconsistency volume of 1989, edited by Priest, Routley and Norman, as a paper entitled “On detonating” (Schotch and Jennings 1989). The point they were making (quite rightly) is that if ex falso is true then negation detonates in inconsistent theories; their every sentence has a validly derivable negation. In Woods’ appropriation of it in the passages I am quoting, the property that detonates is the property of being fictional.
- 12.
On the related problem of resemblance (similarity, isomorphism, homomorphism, etc.) in scientific modeling see Chap. 4, this book.
- 13.
In this eco-cognitive perspective we can even more strongly agree with Morrison’s when she is pretty clear about the excessive habit of labeling fictional scientific models simply because they are superficially seen as “unrealistic”: “Although there is a temptation to categorize any type of unrealistic representation as a ‘fiction’, I have argued that this would be a mistake, primarily because this way of categorizing the use of unrealistic representations tells us very little about the role those representations play in producing knowledge” (Morrison 2009, p. 133).
- 14.
Cf. above, Chap. 1, Sect. 1.3, this book.
- 15.
Cf. also p. 38, Sect. 2.3 of the previous chapter of this book.
- 16.
The reason of my skepticism about the vision of models in terms of the pretence theory can be illustrated taking advantage of some classical but still astounding theses derived from Kantian philosophy and Thom’s mathematical semiophysics, I will treat in the following chapter, Sect. 4.2.
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Magnani, L. (2017). Not Everything in Scientific Cognition Is Evidence-Based. In: The Abductive Structure of Scientific Creativity. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 37. Springer, Cham. https://doi.org/10.1007/978-3-319-59256-5_3
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