Lessons Learned: Overcoming Obstacles to Inference and Synthesis in Atrocity Prevention Research

In this paper, we argue that atrocity prevention (AP) researchers face obstacles to inference and knowledge synthesis in the study of AP strategies and tools. We argue that researchers can begin to address obstacles to inference by using rigorous social-science methods and can address obstacles to knowledge synthesis through greater coordination and transparency about concepts, methods, and data. Our argument proceeds in four parts. First, drawing on a systematic review of three decades of research about AP tools, we survey key analytic obstacles to drawing conclusions about the effects of AP policy. Second, we survey four separate methods that researchers increasingly use to address some of these inferential issues in individual studies. Third, we survey the subsequent obstacles to synthesizing and aggregating conclusions from these studies, despite methodological advances. We conclude by offering recommendations about how researchers can conduct research that would be easier to synthesize across studies and some initial ideas about how analysts can use the existing body of research to inform policy decisions. In particular, we recommend that both researchers and practitioners adopt a “Bayesian approach” to interpreting evidence from the AP literature by thinking in probabilistic terms, using context-specific information about particular cases to refine estimates of the likely outcomes of AP tools based on more general evidence.