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    Barros, D. Benjamin 2013. Negative causation in causal and mechanistic explanation. Synthese, Vol. 190, Issue. 3, p. 449.

    Helgeson, Casey 2013. What Selection Can and Cannot Explain: A Reply to Nanay’s Critique of Sober. Philosophy of Science, Vol. 80, Issue. 1, p. 155.

  • Royal Institute of Philosophy Supplement, Volume 27
  • March 1990, pp. 247-266

Contrastive Explanation*


According to a causal model of explanation, we explain phenomena by giving their causes or, where the phenomena are themselves causal regularities, we explain them by giving a mechanism linking cause and effect. If we explain why smoking causes cancer, we do not give the cause of this causal connection, but we do give the causal mechanism that makes it. The claim that to explain is to give a cause is not only natural and plausible, but it also avoids many of the objections to other accounts of explanation, such as the views that to explain is to give a reason to believe the phenomenon occurred, to somehow make the phenomenon familiar, or to give a Deductive-Nomological argument. Unlike the reason for belief account, a causal model makes a clear distinction between understanding why a phenomenon occurs and merely knowing that it does, and the model does so in a way that makes understanding unmysterious and objective. Understanding is not some sort of super-knowledge, but simply more knowledge: knowledge of the phenomenon and knowledge of its causal history. A causal model makes it clear how something can explain without itself being explained, and so avoids the regress of whys, since we can know a phenomenon's cause without knowing the cause of the cause. It also accounts for legitimate self-evidencing explanations, explanations where the phenomenon is an essential part of the evidence that the explanation is correct, so the explanation can not supply a non-circular reason for believing the phenomenon occurred. There is no barrier to knowing a cause through its effects and also knowing that it is their cause. The speed of recession of a star explains its observed red-shift, even though the shift is an essential part of the evidence for its speed of recession. The model also avoids the most serious objection to the familiarity view, which is that some phenomena are familiar yet not understood, since a phenomenon can be perfectly familiar, such as the blueness of the sky or the fact that the same side of the moon always faces the earth, even if we do not know its cause. Finally, a causal model avoids many of the objections to the Deductive-Nomological model. Ordinary explanations do not have to meet the requirements of the Deductive-Nomological model, because one does not need to give a law to give a cause, and one does not need to know a law to have good reason to believe that a cause is a cause. As for the notorious over-permissiveness of the Deductive-Nomological model, the reason recession explains red-shift but not conversely, is simply that causes explain effects but not conversely, and the reason a conjunction of laws does not explain its conjuncts is that conjunctions do not cause their conjuncts.

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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

D. -H. Ruben 1987. ‘Explaining Contrastive Facts’, Analysis 47.1: 35a–7.

D. Temple 1988. ‘Discussion: The Contrast Theory of Why-Questions’, Philosophy of Science 55: 141–51.

B. van Fraassen 1980. The Scientific Image (Oxford: The Clarendon Press).

J. Worrall 1988. ‘An Unreal Image’, The British Journal for the Philosophy of Science, 35: 6580.

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Royal Institute of Philosophy Supplements
  • ISSN: 1358-2461
  • EISSN: 1755-3555
  • URL: /core/journals/royal-institute-of-philosophy-supplements
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