Abstract
There are two possible realist defense strategies against the pessimistic meta-induction and Laudan’s meta-modus tollens: the selective strategy, claiming that discarded theories are partially true, and the discontinuity strategy, denying that pessimism about past theories can be extended to current ones. A radical version of discontinuity realism is proposed by Gerald Doppelt: rather than discriminating between true and false components within theories, he holds that superseded theories cannot be shown to be even partially true (except insofar they agree with current ones), while present best theories are demonstrably completely true. I argue that this position, running counter both the cumulativity of science and fallibilism, is untenable; it cannot account for the success of past theories, nor for the failures of current theories, and rather than shutting the door to the pessimistic historical objections it opens it wide. The best strategy, instead, joins the selective idea there was both some truth and some falsity in discarded theories, like in current ones, with the moderate discontinuity idea that the truth rate in present best theories is much greater than in past ones.
Similar content being viewed by others
Notes
For instance, Doppelt calls both of them ‘pessimistic meta-induction’; Saatsi distinguishes them, but curiously he calls the meta-modus tollens (MMT) ‘pessimistic meta-induction’.
A similar statement is commonly attributed to Lord Kelvin, but it is not clear whether he actually made it: Horgan (1996, p. 19).
Although here I discuss papers over a span of 9 years, they appear as developments of a unitary conception, and Doppelt never indicates any change of mind with respect to earlier papers.
As we shall see, this wavering reflects another in the exact content of his doctrine.
Interpretation (4) was suggested by Referee #2. But I shall suggest that (2) is more probably the right one.
Both italics are mine.
Although after some wavering, as I will notice.
Including novel retrodictions, or novel explanations: i.e., the derivations of previously known phenomena which were not used in building the theory: see Alai (2014a).
I owe this comment to Reviewer #3.
Instead, if it is not adopted, the theory cannot be considered successful at all, except in merely rephrasing known empirical regularities: Alai (2014b), \({\S }\)6.
Stanford (2006, Chap. 6) also charges the retrospective truth claims of circularity.
This interpretation was also suggested by Referee #2.
My italics.
In Sect. 2 we saw that by “best explanation” he basically means one endowed with the standard theoretical virtues; but this is not crucial here.
In Sect. 2 we saw that by “best explanation” he basically means one endowed with the standard theoretical virtues; but this is not crucial here.
These considerations have been brought to my attention by Reviewer #3.
References
Agazzi, E. (2014). Scientific objectivity and its contexts. Cham: Springer.
Alai, M. (2014a). Novel predictions and the no miracle argument. Erkenntnis, 79(2), 297–326. doi:10.1007/s10670-013-9495-7.
Alai, M. (2014b). Defending deployment realism against alleged counterexamples. In G. Bonino, G. Jesson, & J. Cumpa (Eds.), Defending realism. Ontological and epistemological investigations (pp. 265–290). Boston-Berlin-Munich: De Gruyter.
Alai, M. (2014c). Why antirealists can’t explain success. In F. Bacchini, S. Caputo & M. Dell’Utri (Eds.), Metaphysics and ontology without myths (pp. 48–66). Newcastle upon Tyne: Cambridge Scholars Publishing.
Alai, M. (2014d). Deployment vs. Discriminatory realism. In [2014] New thinking about scientific realism (Cape Town, South Africa; 5-9 August 2014), PhilSci Archive. http://philsci-archive.pitt.edu/10551/.
Bird, A. (2015). Is there meta-scientific knowledge? Against both the no-miracles argument and the pessimistic meta-induction. Draft.
Cartwright, N. (1983). How the laws of physics lie. Oxford: Clarendon and Oxford University.
Chang, H. (2004). Inventing temperature: Measurement and scientific progress. New York: Oxford University Press.
Chang, H. (2012). Is water H \(_{2}\) O? Evidence, pluralism and realism. Dordrecht: Springer.
Cordero, A. (2015). Retention, truth-content and selective realism. Draft.
Devitt, M. (1984). Realism and truth. Oxford: Blackwell.
Devitt, M. (2005). Scientific realism. In F. Jackson & M. Smith (Eds.), The Oxford handbook of contemporary philosophy (pp. 767–791). Oxford: University Press.
Doppelt, G. (2005). Empirical success or explanatory success: What does current scientific realism need to explain? Philosophy of Science, 72, 1076–1087.
Doppelt, G. (2007). Reconstructing scientific realism to rebut the pessimistic meta-induction. Philosophy of Science, 74, 96–118.
Doppelt, G. (2011). From standard scientific realism and structural realism to best current theory realism. Journal for General Philosophy of Science, 42, 295–316.
Doppelt, G. (2013). Explaining the success of science: Kuhn and scientific realists. Topoi, 32, 43–51.
Doppelt, G. (2014). Best theory scientific realism. European Journal for Philosophy of Science, 4, 271–291.
Fahrbach, L. (2011). Theory change and degrees of success. Philosophy of Science, 78, 1283–1292.
Hardin, C., & Rosenberg, A. (1982). In defence of convergent realism. Philosophy of Science, 49, 604–615.
Heisenberg, W. (1955). Das Naturbild der heutigen Physik. Hamburg: Rohwolt.
Horgan, J. (1996). The end of science: Facing the limits of science in the twilight of the scientific age. New York: Broadway Books.
Horgan, J. (2015). Was I wrong about ‘The End of Science’? Scientific American. http://blogs.scientificamerican.com/cross-check/was-i-wrong-about-8220-the-end-of-science-8221/.
Kitcher, P. S. (1993). The advancement of science. Oxford: University Press.
Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press.
Ladyman, J. (2002). Understanding philosophy of science. London: Routledge.
Ladyman, J., & Ross, D. (2007). Chapter 2: Scientific realism, constructive empiricism, and structuralism. In Everything must go: Metaphysics naturalized (pp. 66–129). Oxford: Oxford University Press.
Lakatos, I. (1970). Falsification and the methodology of scientific research programmes. In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge (pp. 91–195). Cambridge, MA: University Press.
Lange, M. (2002). Baseball, pessimistic inductions and the turnover fallacy. Analysis, 62, 281–285.
Laudan, L. (1981). A confutation of convergent realism. Philosophy of Science, 48, 19–49.
Lewis, P. (2001). Why the pessimistic induction is a fallacy. Synthese, 129, 371–380.
Lyons, T. D. (2002). The pessimistic meta-modus ollens. In S. Clarke & T. D. Lyons (Eds.), Recent themes in the philosophy of science. Scientific realism and commonsense (pp. 63–90). Dordrecht: Kluwer.
Musgrave, A. (2006–2007). The ‘Miracle Argument’ for scientific realism. The Rutherford Journal, the New Zealand Journal for the History and Philosophy of Science and Technology, 2. http://www.rutherfordjournal.org/article020108.html.
Netz, R., & Noel, W. (2007). The Archimedes codex: Revealing the secrets of the world’s greatest palimpsest. London: Weidenfeld and Nicolson.
Niiniluoto, I. (1987). Truthlikeness. Dordrecht: Reidel.
Oddie, G. (1986). Likeness to truth. Dordrecht: Reidel.
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251). http://science.sciencemag.org/content/349/6251/aac4716.full.
Peters, D. (2014). What elements of successful scientific theories are the correct targets for “selective” scientific realism? Philosophy of Science, 81, 377–397.
Poincaré, H. (1902). La science et l’hypothèse, Paris : Flammarion. Engl. transl. Science and Hypothesis. New York: Dover Publications 1952.
Popper, K. (1963). Conjectures and refutations: The growth of scientific knowledge. New York: Harper and Row.
Psillos, S. (1999). Scientific realism. How science tracks truth. London: Routledge.
Putnam, H. (1975). The meaning of ‘meaning’. In Id., Mind, language and reality (pp. 215–271). Cambridge, MA: Cambridge University Press.
Putnam, H. (1978). Meaning and the moral sciences. London: Routledge and Kegan Paul.
Rescher, N. (1987). Scientific realism: A critical reappraisal. Dordrecht: Reidel.
Russo, L. (1996). La Rivoluzione dimenticata. Milano: Feltrinelli.
Russo, L. (2003). Flussi e riflussi. Milano: Feltrinelli.
Saatsi, J. T. (2005). On the pessimistic induction and two fallacies. Philosophy of Science, 72, 1088–1098.
Shanks, D. R., Vadillo, M. A., Riedel, B., Clymo, A., Govind, S., Hickin, N., et al. (2015). Romance, risk, and replication: Can consumer choices and risk-taking be primed by mating motives? Journal of Experimental Psychology: General, 144(6), e142–e158.
Shapere, D. (1984). Reason and the search for knowledge. Boston studies in the philosophy of science (Vol. 78). Dordrecht: Reidel.
Stanford, P. K. (2006). Exceeding our grasp: Science, history, and the problem of unconceived alternatives. Oxford: Oxford University Press.
Votsis, I. (2011). The prospective stance in realism. Philosophy of Science, 78, 1223–1234.
Worrall, J. (1989). Structural realism: The best of both worlds? Dialectica, 43, 99–124.
Acknowledgments
I am grateful to José Diez, Vincenzo Fano, Carl Hoefer, and Giuliano Torrengo for useful comments on earlier versions of this paper, and to two anonymous reviewers for this Journal for helpful suggestions both on the general structure and on particular issues.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Alai, M. Resisting the historical objections to realism: Is Doppelt’s a viable solution?. Synthese 194, 3267–3290 (2017). https://doi.org/10.1007/s11229-016-1087-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11229-016-1087-z