Partial explanations in social science’

In Harold Kincaid (ed.), The Oxford Handbook of Philosophy of Social Science. Oxford University Press. pp. 130-153 (2012)
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Abstract
Comparing different causes’ importance, and apportioning responsibility between them, requires making good sense of the notion of partial explanation, that is, of degree of explanation. How much is this subjective, how much objective? If the causes in question are probabilistic, how much is the outcome due to them and how much to simple chance? I formulate the notion of degree of causation, or effect size, relating it to influential recent work in the literature on causation. I examine to what extent mainstream social science methods--both quantitative and qualitative--succeed in establishing effect sizes so understood. The answer turns out to be, roughly: only to some extent. Next, the standard understanding of effect size, even though widespread, still has several underappreciated consequences. I detail some of those. Finally, I discuss the separate issue of explanandum-dependence, which is essential to assessing any cause’s explanatory importance and yet which has been comparatively neglected.
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Archival date: 2015-11-21
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References found in this work BETA
Causality.Pearl, Judea
The Scientific Image.Van Fraassen, Bas C.
Cause and Norm.Hitchcock, Christopher & Knobe, Joshua
Dissecting Explanatory Power.Ylikoski, Petri & Kuorikoski, Jaakko

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Citations of this work BETA
Degree of Explanation.Northcott, Robert
Harm and Causation.Northcott, Robert

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