July 23, 2016

Back in January, it snowed in Chapel Hill. When that happens around here, as you can imagine, things tend to shut down fast. The schools were closed, and we were iced in at home for a couple of days. The kids had a lot of quality Playstation time. Meanwhile, my wife and I ended up sitting across from one another at the kitchen table, arguing. In the end we resolved things by doing something we’d never done before—we co-authored a paper. I’m very pleased to say it was just accepted for publication by Noûs. It builds on some of the ideas in Laurie’s recent book, Transformative Experience, which you should of course buy immediately. While you’re waiting for it to arrive, you can read our joint paper, Transformative Treatments [PDF]. Here’s the abstract:

Contemporary social-scientific research seeks to identify specific causal mechanisms for outcomes of theoretical interest. Experiments that randomize populations to treatment and control conditions are the “gold standard” for causal inference. We identify, describe, and analyze the problem posed by transformative treatments. Such treatments radically change treated individuals in a way that creates a mismatch in populations, but this mismatch is not empirically detectable at the level of counterfactual dependence. In such cases, the identification of causal pathways is underdetermined in a previously unrecognized way. Moreover, if the treatment is indeed transformative it breaks the inferential structure of the experimental design. Transformative treatments are not curiosities or “corner cases”, but are plausible mechanisms in a large class of events of theoretical interest, particularly ones where deliberate randomization is impractical and quasi-experimental designs are sought instead. They cast long-running debates about treatment and selection effects in a new light, and raise new methodological challenges.

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I am Associate Professor of Sociology at Duke University. I’m affiliated with the Kenan Institute for Ethics, the Markets and Management Studies program, and the Duke Network Analysis Center.



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