Process Tracing: To Deepen or to Broaden, and Why it Matters

The purpose of DocuLab is to strengthen the Department's endowment of quantitative and qualitative methodologies of documentary analysis. These allow researchers to understand societal developments and policy decisions starting from the documents that individuals and institutions produce. Such documents may be written (letters, journal articles, chronicles, autobiographies, and of course official documents such as expert reports, legislative bills and acts, treaties, jurisprudence and much more) as well as written transcriptions of oral and other types of communications (press releases, minutes of parliamentary debates, social media feeds, posters, etc.). DocuLab's mission to develop and diffuse these techniques of documentary analysis is supported by the Department's Excellence Project (2023-2027)

Speaker: 

Jeffrey Checkel - European University Institute

In recent years, our research and teaching on process analytics have grown by leaps and bounds. If such analytics are about the collection and analysis of data on processes and dynamics, then we have made important advances in the analysis part.  This is most clearly seen in the growing literature on Bayesian process tracing, which has given us a deeper, getting-closer-to-the-truth method. Yet, to do those analytics well requires rich, high-quality data; consequently, process tracing needs to think harder about this data collection. This means a greater focus on within-process-tracing methods and research ethics. Finally, we need to broaden how we collect and analyse our data by developing a robust interpretive form of process analytics. The next stage in developing process analytics should thus focus on broadening its epistemological basis, the front-end data collection, its research ethics. This agenda will give students of process methods a richer, more ethically grounded, meta-theoretically plural set of tools for measuring and accessing all that cool stuff out there in the social world