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The Reproducibility Working Group

January 29, 2019 - 11:45am

Ford Hall, Room 300

The Reproducibility Working Group is an interdisciplinary collaboration among faculty, post-docs, and graduate students in philosophy, psychology, statistics, and other areas that coalesced at the end of the spring semester after biweekly discussions on questions about reproducibility in psychology hosted by the Minnesota Center for Philosophy of Science. Last semester (Fall 2018), we explored questions about measurement in the context of psychometrics by reading Measuring the Mind: Conceptual Issues in Contemporary Psychometrics (Cambridge University Press, 2005) every other week over lunch together. We finished the semester with a visit and two lectures from Joel Michell (University of Sydney) on the logic of measurement and psychometrics.

This semester we are continuing these discussions with a biweekly lunch discussion on Tuesdays (11:45am-1pm) to study another of these issues in more depth: causal inference. We will be reading a variety of articles offering different perspectives on causal inference, methodology, and reproducibility. The schedule of meetings and readings (to be held in 300 Ford Hall) is:


2/12: TBA
2/26: TBA
3/12: TBA
3/26: TBA
4/9: TBA
4/23: TBA
5/2-5/3: Causal Inference and Data Science, Institute for Research in Statistics and its Applications Annual Conference

Readings are accessible to all University of Minnesota community members (click on the links above). For any questions about access, please contact Amanda Schwartz (

Note: lunch will be provided for participants. New participants please RSVP to Amanda Schwartz ( no later than the Thursday preceding the RGW meeting (e.g., Thursday 1/24 for session on 1/29). Participants are welcome to join for any and all sessions as their schedules permit.

The Reproducibility Working Group is jointly sponsored by the Commons for Research in the Social Sciences, the Institute for Research in Statistics and its Applications, and the Minnesota Center for Philosophy of Science