most scientists are instrumentalists on Sunday and scientific realists the rest of the week
The Epicurean Dealmaker, “Our glassy essence”
http://epicureandealmaker.blogspot.com.es/2013/10/our-glassy-essence.html.
Abstract
The decision whether to have a realist or an anti-realist attitude towards scientific hypotheses is interpreted in this paper as a choice that scientists themselves have to face in their work as scientists, rather than as a ‘philosophical’ problem. Scientists’ choices between realism and instrumentalism (or other types of anti-realism) are interpreted in this paper with the help of two different conceptual tools: a deflationary semantics grounded in the inferentialist approach to linguistic practices developed by some authors (e.g., Sellars, Brandom), and an epistemic utility function that tries to represent the cognitive preferences of scientists. The first tool is applied to two different questions traditionally related to the problem of scientific realism: the non-miracle argument, and the continuity of reference. The second one is applied to the problem of unconceived alternatives, and to the distinction between realist and instrumentalist attitudes towards scientific hypotheses.
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Notes
“Realism requires two distinct elements. It requires belief and it also requires a particular interpretation of that belief”, Fine (1986, p. 176).
Horwich (1990).
Brandom (1994, ch. 5).
Putnam (1981).
Of course, there can be lots of discussions about what is to be a ‘good explanation’ and its connection to predictions, but they will distract us from the specific point I want to make, so I shall use in my argument the most naïve version of the nomologico-deductive schema.
I employ this ‘Bayesian’ reconstruction of the idea of ‘surprisingness’, but each reader can replace it for his or her favourite one.
Of course, philosophers can discuss about what an explanation consists in, what is its relation to prediction, etc., etc. But this is (at best) an additional clarification of the work of scientists, whereas ‘explaining the success of T’ is, if my analysis is right, exactly that work, not a clarification of it.
Actually, it seems even clearer that the best explanations of the empirical success of some past scientific theories do not often come from philosophical arguments, but from the scientific theories that supersede the former ones. For example, Newton’s gravitation theory offered a sensational explanation of why Kepler’s theory of planetary movements was so accurate (though not perfectly so), like Einstein’s relativity explained in a superb way why Newtonian mechanics is so empirically adequate in describing the movements of not-too-fast and not-too-heavy bodies. Again, this shows that you need scientific arguments to explain the success of science, rather than philosophical ones
This is the famous Laudan’s ‘pessimistic meta-induction’; cf. Laudan (1981).
Of course, anti-realist defend just the contrary; cf. Chang (2012)
This (very simplified) analysis of the semantics of referential terms is inspired in Brandom (1994, ch. 5).
Technically, (6) logically follows from (8), but not viceversa, but this is because of some technical reasons about doxastic logic that are not relevant for my argument.
Furthermore, those ‘causal capacities’ would be after all nothing but additional predicates to be included in formulas (4)–(9), and so logic itself would be as powerless to allow us to derive any relevant difference from causal predicates as it is regarding any other type of predicates.
See again Chang (2012) for a nice historical illustration.
One referee has pointed out that the continuity of reference is not so much something that philosophical realism has to explain, as something that, if true, will count as an argument in favour of realism. I do not deny this, though I doubt that it reflects a unanimous philosophical view about the connection between the problem of continuity and the problem of realism. But, assuming the referee’s point, it does not count against my argument, for I’m not criticising realism, but the idea that the arguments in favour of realism are fundamentally ‘philosophical’, rather than scientific. So, if the continuity of reference is a datum supporting realism, my point is that it will be scientists, nor philosophers, the ones that have to decide whether continuity exists and in what cases.
By the way, an analysis of scientists’ choice between (8) and (9) under the pragmatic approach suggested here would be in line with the view of ‘rhetoric as the strategic use of language’ I have advanced in Zamora Bonilla (2006), though applied to a totally different case (there, the topic was the choice of one interpretation or another of an experimental result).
Elsewhere (e.g., Zamora Bonilla 2002a) I have used the hypotheses that the scientists’ utility functions combine two elements, an epistemic and a social one, which I identify basically with recognition from their colleagues. This ‘social’ part will be irrelevant for the rest of my argument here.
I presented this definition in Zamora Bonilla (1996). For more details, see Zamora Bonilla (2013). Independently, the formula p(X & Y)/p(XvY) became later a standard definition of coherence, after Olsson (2002); similar results could be proved with other definitions of coherence or similarity, but I think the combination of power and simplicity of that one justifies its choice. My definition is close in spirit to other approaches to verisimilitude (the notion that different theories can be farther or closer to the truth; see Niiniluoto 1987), but combines in a single measure of ‘how closer to the whole truth a theory seems to be’ what in other approaches, like Ilkka Niiniluoto’s, is decomposed into a notion of ‘objective distance to the truth’ and a notion of ‘estimated distance’. My own point of view is that any relevant notion of ‘similarity’ contains always some subjective factors, which in my definition are partly taken into account by the fact that p represents a subjective probability function.
For simplicity, the symbol ‘\(\propto \)’ will be replaced by ‘=’ in the reminder of the paper.
Actually, as John Norton (2014) has argued, scientists often try toprove their theories from previously known empirical facts or laws (for example, Newton offered a ‘demonstration’ of the law of gravity taking Kepler’s laws as premises), but if this were true at face value, it would entail that theories are not falsifiable (at least, while the empirical laws from which they are mathematically deduced are not rejected), nor can do more predictions than those derivable by the previous empirical laws alone. I will offer below a different interpretation of this kind of ‘demonstrative’ arguments by scientists.
Stanford (2006).
I do not deny that logico-mathematical truths play an important role in scientific argumentation and discovery, but I don’t think they can be identified with ‘theories’ in any relevant sense, at least when they are taken in isolation. They are, at most, important elements of theories or research programmes, and above all, rules or principles for mathematical deduction.
This is a rewording of the idea that extraordinary claims demand extraordinary evidence.
This would be my suggested interpretation of Norton’s claim I have referred to above, according to which scientists often use the empirical evidence to ‘prove’ their theories, and not only to test them.
Hence, in connection to our discussion in Sect. 2, it’s not only false that ‘scientific discourse’ is ontologically or epistemologically dull, so to say, and is in need of a ‘philosophical interpretation’ in order to derive from it rational answers about what there is, what is true, and how to know it; the case is also that philosophical arguments can play a role within scientific discourse in order to argue about the plausibility or naturalness of certain claims. I think this is specially true in the case of scientific revolutions, but of course, a detailed historical study would be necessary to assess this idea.
One referee has suggested that an instrumentalist would be someone who does not even assign a probability to theories. I see no much difference in practice between that and what I am proposing: that not taking into account the probability of a theory, even if it is very low, would count as having an instrumentalist attitude. Whether you don’t take probability into account because you think there is a probability but ignore it, or because you think there is no probability, would lead to the same choices.
For simplicity, I will use the expression “w\({\in }\)E” as an abbreviation of “a point in the logical space that satisfies E”). “Vs(T,w)” would refer, then, to the empirical verisimilitude T would have if the future evidence uniquely selects w as the real world.
Especially if we consider the sophisticated version of our utility function briefly discussed a few pages above, i.e., replacing Vs(T,E) with Vs(T,E(T)). Cf. Zamora Bonilla (2002b).
Though it is not as directly relevant to the discussion about realism as the other questions examined so far in this paper, I would also like to mention that the hypothesis that Vs more or less correctly represents the epistemic preferences of real scientists can be used to make sense of the fact (mentioned in Sect. 2.2) that prediction of unknown empirical results is more valuable than mere ‘accommodation’ of those previously known. The reason is that scientists would prefer, as we have seen, to develop new theories by starting with those whose assumptions that seem most likely to them. Hence, accommodating an empirical fact will demand to replace some of the theory’s assumptions with another which is less likely, hence reducing the maximum value of p, and thence of Vs, that the theory can get from E. This explanation is coherent with some other recent arguments about the superiority of prediction over accommodation, in particular those linking the former to the expectation of future empirical success (see Douglas and Magnus 2013, for a survey).
References
Bartels, A. (2010). Explaining referential stability of physics concepts: The semantic embedding approach. Synthese, 41, 267–281.
Brandom, R. (1994). Making it explicit. Cambridge (Mass.): Harvard University Press.
Bueno, O. (2008). Structural realism, scientific change, and partial structures. Studia Logica, 89, 213–235.
Chang, H. (2012). Is water \(H_{2}O?\). Dordrecht: Springer.
Douglas, H., & Magnus, P. D. (2013). State of the field: Why novel prediction matters. Studies in History and Philosophy of Science, 44, 580–589.
Fine, A. (1986). The shaky game. Chicago: University of Chicago Press.
Frost-Arnold, G. (2010). The no-miracles argument for realism: Inference to an unacceptable explanation. Philosophy of Science, 77, 35–58.
Horwich, P. (1982). Probability and evidence. Cambridge: Cambridge University Press.
Horwich, P. (1990). Truth. Oxford: Blackwell.
Ladyman, J. (2007). On the identity and diversity of individuals. The Proceedings of the Aristotelian Society, Supplementary, 81, 23–43.
Laudan, L. (1981). A confutation of convergent realism. Philosophy of Science, 48, 19–49.
Niiniluoto, I. (1987). Truthlikeness. Dordrecht: Reidel.
Norton, J. D. (2014). A material dissolution of the problem of induction. Synthese, 191, 671–690.
Olsson, E. J. (2002). What is the problem of coherence and truth? The Journal of Philosophy, 99, 246–278.
Psillos, S. (1999). Scientific realism: How science tracks truth. London: Routledge.
Putnam, H. (1981). Reason, truth and history. Cambridge: Cambridge University Press.
Stanford, P. K. (2006). Exceeding our grasp: Science, history, and the problem of unconceived alternatives. Oxford: Oxford University Press.
Worrall, J. (1989). Structural realism: The best of both worlds? Dialectica, 43, 99–124.
Worrall, J. (2007). Miracles and models: Why reports of the death of structural realism may be exaggerated. Royal Institute of Philosophy Supplements, 82(61), 125–154.
Zamora Bonilla, J. P. (1996). Verisimilitude, structuralism and scientific progress. Erkenntnis, 44, 25–47.
Zamora Bonilla, J. P. (2002a). Scientific inference and the pursuit of fame: A contractarian approach. Philosophy of Science, 69, 300–323.
Zamora Bonilla, J. P. (2002b). Verisimilitude and the dynamics of scientific research programmes. Journal for General Philosophy of Science, 33, 349–368.
Zamora Bonilla, J. P. (2006). Rhetoric, induction, and the free speech dilemma. Philosophy of Science, 73, 175–193.
Zamora Bonilla, J. P. (2013). Why are good theories good? Reflections on epistemic values, confirmation, and formal epistemology. Synthese, 190, 1533–1553.
Acknowledgments
The author thanks Spain’s government research projects FFI2011-23267, PRX14-00007 and FFI2014-57258-P.
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Zamora Bonilla, J.P. Realism versus anti-realism: philosophical problem or scientific concern?. Synthese 196, 3961–3977 (2019). https://doi.org/10.1007/s11229-015-0988-6
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DOI: https://doi.org/10.1007/s11229-015-0988-6