To clarify, I suspect we have some agreement on (social movement) case studies: I do think they can provide evidence towards causation—literally that one should update their subjective Bayesian beliefs about causation based on social movement case studies. However, at least to my understanding of the current methods, they cannot provide causal identification, thus vastly limiting the magnitude of that update. (In my mind, to probably <10%.)
What I’m struggling to understand fundamentally is your conception of the quality of evidence. If you find the quality of evidence of the health behavior literature low, how does that compare to the quality of evidence of SI’s social movement case studies? One intuition pump might be that the health behavior literature undoubtedly contains scores of cross-sectional studies, which themselves could be construed as each containing hundreds of case studies, and these cross-sectional studies are still regarded as much weaker evidence than the scores of RCTs in the health behavior literature. So where then must a single case study lie?
For what it’s worth, in reflecting on an update which is fundamentally about how to make causal inferences, it seems like being unfamiliar with common tools for causal inference (eg, instrumental variables) warrants updating towards an uninformed prior. I’m not sure if they’ll restore your confidence, but I’d be interested to hear.
Thank you for your replies, Jamie, I appreciate the discussion. As a last point of clarification when you say ~40%, does this, for example, mean that if a priori I was uninformed on momentum v complacency and so put 50/50% credence on either possibility, that a series of case studies might potentially update you to 90/10%?
I don’t disagree—but my point with this intuition pump is the strength of inference a case study, or even series of case studies, might provide on any one of those questions.