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Data Science Studies seminar series: "Remaking epistemic hierarchies in the era of data science"
WhenThursday, Nov 1, 2018, 3:30 – 4:30 p.m.
WhereWRF Data Science Studio, 6th Floor of the Physics/Astronomy Tower (…)
Event typesLectures/Seminars
Event sponsorseScience Institute
Science, Technology & Society Studies

The Data Then and Now series explores the social and organizational history of data and data practices in order to better understand the current data-intensive moment through its antecedents and continuities. Everyone interested is welcome to attend.

The series features invited guest lectures by notable science and technology studies scholars. Our inaugural lecture, “Give me a laboratory: Remaking epistemic hierarchies in the era of data science," will be delivered by Dr. Nicole Nelson of the Department of Medical History and Bioethics at the University of Wisconsin-Madison.

Nicole C. Nelson

Give me a laboratory: Remaking epistemic hierarchies in the era of data science

In Bruno Latour’s now classic essay “Give me a laboratory and I will raise the world,” he argues that laboratories are powerful sites for knowledge production because they allow scientists to control, purify, and dissect natural phenomena in a space shielded from the scrutiny of the public. But like all styles of knowledge production, laboratory science is not without its weaknesses: controlled conditions, for example, can be quite difficult to create even in these spaces. This talk will examine the NIH’s recently introduced policies on rigor and reproducibility as a site to study what biomedical scientists see as the problems with present-day laboratory science. The NIH’s policies illustrate two conflicting views about what’s wrong with the current state of laboratory science, both of which I argue indirectly privilege alternative epistemic styles that seek truth in data. One view sees current problems in reproducing research results as attributable to inadequate controls that can be rectified through greater standardization. The other views standardization as the source of the problem rather than the solution, and argues for a greater embrace of heterogeneity. I argue that these solutions—designed to shore up the integrity of the laboratory—may instead contribute to strengthening the data sciences.

Nicole C. Nelson is an Assistant Professor in the Department of Medical History and Bioethics at the University of Wisconsin--Madison. Her first book, Model Behavior, used laboratory ethnography to study how animal behavior geneticists’ beliefs about the complexity of psychiatric disorders were reflected in their research with mouse models. She is currently on leave at the Radcliffe Institute at Harvard University, working on a new project on the reproducibility crisis.

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