When do Variables Overlap?

I spent the past two days preparing comments on a very interesting paper by Vera Hoffmann-Kolss for the upcoming Society for the Metaphysics of Science meeting. Thinking through the paper got me freshly confused about some matters that I had thought settled, and so I thought I’d write up a blog post on those confusions in an attempt to sort them out.

It’s tempting to think that counterfactual dependence suffices for causation. But this can’t be quite right. I both played cards and played poker. Had I not played cards, I wouldn’t have played poker. So there is counterfactual dependence between my playing poker and my playing cards. But my playing cards didn’t cause me to play poker. The relationship between my playing cards and my playing poker is constitutive, not causal.

Sophisticated counterfactual theories of causation, therefore, do not say that counterfactual dependence suffices for causation. Rather, what they say is that counterfactual dependence between distinct events suffices for causation. By ‘distinct’, we mean a bit more than ‘non-identical’. The event of my playing poker is not identical to the event of my playing cards. (If you doubt this, note that they differ causally. I played poker because I didn’t have a pinochle deck—I usually play pinochle. But I certainly didn’t play cards because I didn’t have a pinochle deck.) Rather, ‘distinct’ in this context means something more like ‘not logically related’. If two events are not distinct, then let’s say that they overlap.

Worries about overlap plague other theories of causation, too. My playing poker is a minimally sufficient condition for my playing cards, so—unless overlapping conditions are specifically excluded—Mackie’s account of causation will deem them causally related.

Today, I’ll be exploring this problem as it plays out for those who, like myself, think that the causal relata are variable values. For such theorists, the problem is to say when variables are distinct, and when they overlap.

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