Contrastive Explanation

Abstract
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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DOI 10.1017/S1358246100005130
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References found in this work BETA

Philosophical Papers.David K. Lewis - 1983 - Oxford University Press.
An Unreal Image. [REVIEW]John Worrall - 1984 - British Journal for the Philosophy of Science 35 (1):65-80.

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Citations of this work BETA

Truthmakers for Negative Truths.George Molnar - 2000 - Australasian Journal of Philosophy 78 (1):72 – 86.
Causation and Models of Disease in Epidemiology.Alex Broadbent - 2009 - Studies in History and Philosophy of Science Part C 40 (4):302-311.
Explanation, Understanding, and Unrealistic Models.Frank Hindriks - 2013 - Studies in History and Philosophy of Science Part A 44 (3):523-531.
Deflationism, Conceptual Explanation, and the Truth Asymmetry.David Liggins - 2016 - Philosophical Quarterly 66 (262):84-101.

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