Robert Northcott

This is a chapter written for a popular audience, in which I use poker as a convenient illustration of probability, determinism and counterfactuals. More originally, I also discuss the roles of rationality versus psychological hunches, and explain why even in principle game theory cannot provide us the panacea of a perfect winning srategy. (N.B. The document I have uploaded here is slightly longer than the abbreviated version that appears in the book, and also differs in a few other minor details.)

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.