Social scientists distinguish between predictive and causal research. While this distinction clarifies the aims of two research traditions, this clarity is being blurred by the introduction of machine learning (ML) algorithms. Although ML excels in prediction, scholars are increasingly using ML not only for prediction but also for causation. While using ML for causation appears as a category mistake, this article shows that there is a third kind of research problem in which causal and predictive inference form an intricate synergy.

Podcast interview with Yan Long, an Assistant Professor of Sociology at UC Berkeley specializing in the politics of public health in China. Formerly holding the same position at Indiana University and serving as a Postdoctoral Fellow at the Stanford Center for Philanthropy and Civil Society, she earned her PhD at the University of Michigan and her master’s and bachelor’s degrees at Beijing University.

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Abstract: This talk focuses on the key role of medical experts in changing ideas about gender and the body in Czechoslovakia in the aftermath of the political upheaval of the 1960s. The fashioning of one’s body and its cultivation, criticized as a bourgeois holdover in the Stalinist 1950s, came to be demanded from below and promoted from above as part of socialist lifestyle in the 1970s.

What is the role and impact of private firms in monitoring and enforcing international trade law? Professor Ryan Brutger recently sat down with Daniel Lobo, Sociology PhD Student and Social Science Matrix Communications Scholar, for a podcast to discuss Ryan's new article, "Litigation for Sale: Private Firms and WTO Dispute Escalation." This article presents a theory of lobbying by firms for trade liberalization, not through political contributions, but instead through contributions to the litigation process at the World Trade Organization.

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