Abstract
The D-N model of explanation, Inductive-statistical explanations, causal explanations, explanation as unification pragmatic explanation and action explanations are presented and discussed.
The word ‘explanation’ is used in different ways in different situations. There are two fundamental conflicts in the debates over explanation. The first is whether or not there is a general model that applies to all kinds of scientific explanation. The second fundamental dispute concerns whether the concept of scientific explanation contains a contextual component. The DN-model is still the starting point for most who think that there is a common form for all explanations, albeit all agree that it needs modifications.
Hempel and also most of his critics have taken for granted that the concept of scientific explanation is a non-contextual concept, whereas e.g. Achinstein and van Fraassen have claimed that the contextual component is essential. The consequence of this latter view is that explanatory force of a theory cannot be used in evaluating the theory, since the explanatory force is relative to the background knowledge of those receiving the explanation. On the other hand, one could argue that there is a certain basic perspective shared by all active scientists in a given discipline, which is sufficient for the discussion of a theory’s explanatory force independently of context, within that discipline.
‘After the professor’s explanation we were just as confused as before, only now on a higher level.’
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Notes
- 1.
These principles are the following: (i) individuals of the same species struggle for survival and the chance to reproduce, and those best adapted to their environment produce more offspring, and (ii) genetic variation in a species occurs randomly.
- 2.
Carl Hempel (1905–1998) was born in Germany and worked in USA.
- 3.
It is doubtful whether we really should call this a law, because (i) it is a qualitative statement, and (ii) there are exceptions. But Hempel and Oppenheim didn’t mention any strictures of what to count as a law and their own example is similar in these respects. And the problem here under scrutiny doesn’t depend on these aspects.
- 4.
Friedman, M. (1974). Explanation and scientific understanding. Journal of Philosophy, 71, 5–19.
- 5.
Kitcher, P. (1981). Explanatory unification. Philosophy of Science, 48, 507–31.
- 6.
It is not easy to exactly describe what is meant by a genuinely random event. Even most random events, e.g. computer generation of random numbers, can be shown to be determined by some complicated rule. One definition, due to Chaitin, is to say that a sequence is random if it is not possible to formulate an algorithm that produces the sequence and such that the algorithm is shorter than the sequence itself.
- 7.
Peter Railton has observed that the reference class problem can be avoided in cases where probabilities are interpreted as propensities, see Railton (1978). And since transition probabilities in quantum mechanics can be calculated without knowledge about frequencies, they can be viewed as propensities.
- 8.
- 9.
Kitcher, P., & Salmon, W. (1987). Van Fraassen on explanation. Journal of Philosophy, 84, 315–330.
Further Reading
Achinstein, P. (1981). Can there be a model for explanation? Theory and Decision, 13, 201–227.
Achinstein, P. (1983). The nature of explanation. New York: Oxford University Press.
Cartwright, N. (1999). The dappled world. A study of the boundaries of science. Cambridge: Cambridge University Press.
Davidson, D. (1980 [1963]). Actions, reasons, and causes. In Essays on actions and events (pp. 3–20). New York: Clarendon Press.
Hempel, C. (1965). Aspects of scientific explanation and other essays in the philosophy of science. New York: Free Press.
Hillel-Ruben, D. (Ed.). (1993). Explanation. Oxford readings in philosophy. Oxford: Oxford University Press.
Pitt, W. (Ed.). (1988). Theories of explanation. Oxford: Oxford University Press.
Railton, P. (1978). A deductive-nomological model of probabilistic explanation. Philosophy of Science, 45, 206–226.
Salmon, W. (1984). Scientific explanation and the causal structure of the world. Princeton: Princeton University Press.
Salmon, W. (1998). Causality and explanation. Oxford: Oxford University Press.
van Fraassen, B. (1980). The scientific image. Oxford: Clarendon Press.
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Johansson, LG. (2016). Explanations. In: Philosophy of Science for Scientists. Springer Undergraduate Texts in Philosophy. Springer, Cham. https://doi.org/10.1007/978-3-319-26551-3_8
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