Abstract
Building upon the insights of the previous chapter concerning the nature of explanation and its relation to understanding this chapter argues for a close connection between explanation and evidential support. That is to say, this chapter argues that the degree to which a given body of evidence supports believing that a particular proposition is true depends upon how well that proposition explains the evidence or is explained by the best explanation of that evidence. The upshot of this explanationist view of evidential support is that explanation is an integral component of epistemic justification. As a result of detailing this explanationist view of evidential support, this chapter offers a clear conception of when we should accept claims in science as well as an account of epistemic justification more generally. Thus, the chapter establishes a very close connection between scientific inference and the justification we might have for any of our beliefs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Similar considerations apply to our knowledge of the explanatory hypotheses generated from theories and our knowledge of laws of nature.
- 2.
Here we are concerned with the sort of knowledge that is gained in a particular scientific context—how a theorist can come to know that a particular theory is true. Later, in Chap. 15, we will discuss how one can gain scientific knowledge via testimony from others whether this is through studying the written works of others or being told directly about the theories and their claims, supporting evidence, and so on.
- 3.
- 4.
See Sober (2015) for discussion of the many historical uses and defenses of Ockham’s razor as a method of theory selection.
- 5.
Despite its ubiquity in the sciences, some question the veracity of IBE. We will consider some of the primary objections that have been leveled at IBE in Chap. 14. We will see that these objections are not persuasive.
- 6.
Presumably, we come to have knowledge of laws of nature by either coming to know a theory of which they are a part or by inferring them from numerous known theories which are themselves best explained by the truth of the law. Hence, IBE is integral to this aspect of our scientific knowledge as well.
- 7.
- 8.
See Beebe (2009), Lacey (2005), Lipton (2004), Longino (1990), Lycan (1988), Kuhn (1977), McAllister (1996), McMullin (1982), Quine and Ullian (1978), Thagard (1978), and Vogel (1990) for a sampling of the explanatory virtues that have been proposed in various scientific contexts and the literature on the nature of explanation. Some might question whether all of the virtues listed are distinct—for example, some claim that predictive power is what separates ad hoc theories from those that are not (Popper 1959; Psillos 1999). As a result, they might question whether predictive power and non-ad hocness are actually two virtues rather than one. Fortunately, for our purposes it is sufficient to simply have a grasp of what some of the most commonly cited explanatory virtues are.
- 9.
For more on this see Lipton (2004).
- 10.
This claim is somewhat controversial because some think appeal to likelihood ratios alone may be the key to medical diagnosis. Although it is plausible that likelihood ratios can be important tools in medical diagnosis (see Grimes and Schulz 2005), it is not clear that even their use cannot be accounted for under the umbrella of IBE (see Chap. 12). For present purposes, it is enough to note that it has been claimed that IBE is the primary method of medical diagnosis, and this claim has some plausibility.
- 11.
Despite its widespread use in science and everyday life, IBE is not without its critics. See van Fraassen (1989), Ladyman et al. (1997), Roche and Sober (2013), and Wray (2008). One of the lines of criticism many find particularly troubling is the claim that IBE leads to probabilistic incoherence. In other words, critics charge that IBE is inconsistent with accepted theories of probabilistic reasoning such as Bayesianism. For a survey of responses to objections to IBE see Douven (2011). For responses to the claim that IBE runs afoul of probabilistic reasoning see Lipton (2004), McCain and Poston (2014), McGrew (2003), Okasha (2000), Psillos (1999), and Weisberg (2009). Some (Huemer 2009; Poston 2014) even go so far as to argue that without IBE probabilistic reasoning, including Bayesian confirmation theory, straightforwardly falls prey to the skeptical problem of induction. We will explore criticisms of IBE as well as responses to those criticisms more fully in Chap. 14.
- 12.
- 13.
- 14.
- 15.
This approach is influenced by earlier explanationist views such as Harman (1973) where p is justified when it explains or is explained by one’s evidence. Notably, the approach here does not say that p is justified when it is explained by one’s evidence though. Rather, it holds that p is justified when it best explains S’s evidence or when it would be explained by the best explanation of S’s evidence. The difference here is subtle, but important.
- 16.
For a full development and sustained defense of the sort of account of evidential support we are sketching here see McCain (2014).
- 17.
One might worry whether this proposition is really part of the best explanation of Jeff’s evidence because of concerns having to do with external world skepticism (the view that we cannot know or have good reason to believe propositions about the world around us). There are good reasons for thinking the ordinary propositions that we believe are better explanations than their skeptical rivals. Detailing these reasons is outside of the scope of this chapter, but we will return to this issue in Chap. 11 when we discuss, and respond to, the threat that external world skepticism poses for our scientific knowledge.
- 18.
- 19.
One might worry about how a proposition like <every second grade teacher is a teacher> can explain any feature of someone’s evidence. While it is true that <every second grade teacher is a teacher> cannot offer much by way of a causal explanation of Florence’s evidence, explanation should not be restricted to causal explanations when it comes to Explanationism . The relevant notion of explanation here is the sort we appealed to in our working model in the previous chapter—it is a matter of providing information about dependency relations. It is not implausible to think that the truth of <every second grade teacher is a teacher> does help explain the dependency relation Florence finds herself aware of when she recognizes that the predicate term of this proposition is contained in the subject term.
- 20.
We can assume here that Bert knows there will be more emeralds observed in addition to those which have been observed so far.
- 21.
Whether this regularity is itself a law of nature or some other, perhaps contingent, regularity does not matter for the present purpose.
- 22.
We are assuming that in this case Bert will be making his next observation of a swan from a random sample. Things would be different if he were making an observation from a sample he has reason to believe is biased in some way.
- 23.
For further articulation and defense of why large probabilities explain better than smaller ones see Strevens (2000).
References
Achinstein, P. (2001). The book of evidence. New York: Oxford University Press.
Adler, J. (1994). Testimony, trust, knowing. Journal of Philosophy, 91, 264–275.
Beebe, J. (2009). The abductivist reply to skepticism. Philosophy and Phenomenological Research, 79, 605–636.
Boyd, R. (1981). Scientific realism and naturalistic epistemology. PSA, 1980(2), 613–662.
Boyd, R. (1984). The current status of scientific realism. In J. Leplin (Ed.), Scientific realism (pp. 41–82). Berkeley: University of California Press.
Brewer, W. F., Chinn, C. A., & Samarapungavan, A. (2000). Explanation in scientists and children. In F. Keil & R. A. Wilson (Eds.), Explanation and cognition (pp. 279–298). Cambridge, MA: MIT Press.
Conee, E. (1998). Seeing the truth. Philosophy and Phenomenological Research, 58, 847–857.
Conee, E., & Feldman, R. (2008). Evidence. In Q. Smith (Ed.), Epistemology: New essays (pp. 83–104). Oxford: Oxford University Press.
Darwin, C. (1859/1962). The origin of species. New York: Collier.
Dascal, M. (1979). Conversational relevance. In A. Margalit (Ed.), Meaning and use (pp. 153–174). Dordrecht: Kluwer.
Douven, I. (2011). Abduction. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring 2011 Edition). http://plato.stanford.edu/archives/spr2011/entries/abduction/
Enoch, D., & Schechter, J. (2008). How are basic belief-forming methods justified? Philosophy and Phenomenological Research, 76, 547–579.
Fricker, E. (1994). Against gullibility. In B. K. Matilal & A. Chakrabarti (Eds.), Knowing from words (pp. 125–161). Dordrecht: Kluwer.
Gauch, H. G., Jr. (1992). Statistical analysis of regional yield trials: AMMI analysis of factorial designs. New York: Elsevier.
Gauch, H. G., Jr. (2012). Scientific method in brief. Cambridge, UK: Cambridge University Press.
Glymour, C. (1984). Explanation and realism. In J. Leplin (Ed.), Scientific realism (pp. 173–192). Berkeley: University of California Press.
Goodman, N. (1965). Fact, fiction, and forecast. Cambridge, MA: Harvard University Press.
Goodman, N. (1978). Ways of worldmaking. Cambridge, MA: Harvard University Press.
Gopnik, A. (1998). Explanation as orgasm. Minds and Machines, 8, 101–118.
Grimes, D. A., & Schulz, K. F. (2005). Refining clinical diagnosis with likelihood ratios. The Lancet, 365, 1500–1505.
Harman, G. (1965). The inference to the best explanation. Philosophical Review, 74, 88–95.
Harman, G. (1973). Thought. Princeton: Princeton University Press.
Harman, G. (1986). Change in view. Cambridge, MA: MIT Press.
Harré, R. (1986). Varieties of realism. Oxford: Blackwell.
Hintikka, J. (1998). What is abduction? The fundamental problem of contemporary epistemology. Transactions of the Charles S. Peirce Society: A Quarterly Journal in American Philosophy, 34, 503–533.
Hobbs, J. R. (2004). Abduction in natural language understanding. In L. Horn & G. Ward (Eds.), The handbook of pragmatics (pp. 724–741). Oxford: Blackwell.
Huemer, M. (2009). Explanationist aid for the theory of inductive logic. British Journal of Philosophy of Science, 60, 345–375.
Janssen, M. (2002). Reconsidering a scientific revolution: The case of Einstein versus Lorentz. Physics in Perspective, 4, 421–446.
Josephson, J. R., & Josephson, G. S. (Eds.). (1994). Abductive inference. Cambridge, UK: Cambridge University Press.
Keil, F. C., & Wilson, R. A. (2000). Explaining explanation. In F. C. Keil & R. A. Wilson (Eds.), Explanation and cognition (pp. 1–18). Cambridge, MA: MIT Press.
Kuhn, T. S. (1977). The essential tension: Selected studies in scientific tradition and change. Chicago: University of Chicago Press.
Lacey, H. (2005). Is science value free? Values and scientific understanding (2nd ed.). London: Routledge.
Ladyman, J., Douven, I., Horsten, L., & van Fraassen, B. C. (1997). A defence of van Fraassen’s critique of abductive inference: Reply to Psillos. Philosophical Quarterly, 47, 305–321.
Lipton, P. (1998). The epistemology of testimony. Studies in History and Philosophy of Science, 29, 1–31.
Lipton, P. (2004). Inference to the best explanation (2nd ed.). New York: Routledge.
Longino, H. (1990). Science as social knowledge. Princeton: Princeton University Press.
Lycan, W. G. (1988). Judgement and justification. Cambridge, UK: Cambridge University Press.
Lycan, W. G. (2002). Explanation and epistemology. In P. Moser (Ed.), The Oxford handbook of epistemology (pp. 408–433). Oxford: Oxford University Press.
Lycan, W. G. (2012). Explanationist rebuttals (coherentism defended again). Southern Journal of Philosophy, 50, 5–20.
Markie, P. J. (2013). Rational intuition and understanding. Philosophical Studies, 163, 271–290.
Matthews, M. (2015). Science teaching: The contribution of history and philosophy of science (2nd ed.). New York: Routledge.
McAllister, J. W. (1996). Beauty and revolution in science. Ithaca: Cornell University Press.
McCain, K. (2013). Explanationist evidentialism. Episteme, 10, 299–315.
McCain, K. (2014). Evidentialism and epistemic justification. New York: Routledge.
McCain, K. (2015). Explanationism defended on all sides. Logos & Episteme, 6, 333–349.
McCain, K., & Poston, T. (2014). Why explanatoriness is evidentially relevant. Thought, 3, 145–153.
McGrew, T. (2003). Confirmation, heuristics, and explanatory reasoning. British, Journal for the Philosophy of Science, 54, 553–567.
McMullin, E. (1982). Values in science. PSA 1982, 2, 3–28.
McMullin, E. (1992). The inference that makes science. Milwaukee: Marquette University Press.
Minnameier, G. (2004). Peirce-suit of truth—Why inference to the best explanation and abduction ought not to be confused. Erkenntnis, 60, 75–105.
Moser, P. K. (1989). Knowledge and evidence. Cambridge, UK: Cambridge University Press.
Newton, I. (1687/1999). The Principia: Mathematical principles of natural philosophy (trans: Cohen, I. B. & Whitman, A.). Berkeley: University of California Press.
Okasha, S. (2000). Van Fraassen’s critique of inference to the best explanation. Studies in History and Philosophy of Science, 31, 691–710.
Pitt, J. C. (1988). Galileo, rationality and explanation. Philosophy of Science, 55, 87–103.
Popper, K. R. (1959). The logic of scientific discovery. London: Hutchinson.
Poston, T. (2014). Reason & explanation: A defense of explanatory coherentism. New York: Palgrave-MacMillan.
Psillos, S. (1999). Scientific realism: How science tracks truth. London: Routledge.
Quine, W. V. O., & Ullian, J. S. (1978). The web of belief (2nd ed.). New York: Random House.
Roche, W., & Sober, E. (2013). Explanatoriness is evidentially irrelevant, or inference to the best explanation meets Bayesian confirmation theory. Analysis, 73, 659–668.
Sellars, W. (1963). Science, perception and reality. Atascadero: Ridgeview Publishing.
Sober, E. (2015). Ockham’s razors: A user’s manual. Cambridge, UK: Cambridge University Press.
Strevens, M. (2000). Do large probabilities explain better? Philosophy of Science, 67, 366–390.
Thagard, P. (1978). The best explanation: Criteria for theory choice. Journal of Philosophy, 75, 76–92.
van Fraassen, B. C. (1989). Laws and symmetry. Oxford: Oxford University Press.
Vogel, J. (1990). Cartesian skepticism and inference to the best explanation. Journal of Philosophy, 87, 658–666.
Weisberg, J. (2009). Locating IBE in the Bayesian framework. Synthese, 167, 125–143.
Wilson, R. A., & Keil, F. C. (2000). The shadows and shallows of explanation. In F. C. Keil & R. A. Wilson (Eds.), Explanation and cognition (pp. 87–114). Cambridge, MA: MIT Press.
Wray, K. B. (2008). The argument from underconsideration as grounds for anti-realism: A defence. International Studies in the Philosophy of Science, 22, 317–326.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
McCain, K. (2016). From Explanation to Knowledge. In: The Nature of Scientific Knowledge. Springer Undergraduate Texts in Philosophy. Springer, Cham. https://doi.org/10.1007/978-3-319-33405-9_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-33405-9_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-33403-5
Online ISBN: 978-3-319-33405-9
eBook Packages: Religion and PhilosophyPhilosophy and Religion (R0)