Joanna Radin, Ph.D. will speak on Tuesday, June 9, 2020 at 2:00 PM ET. This program will be live-streamed globally, and archived, by NIH VideoCasting. Dr. Radin is Associate Professor, Program in History of Science and Medicine, Yale University. Circulating Now interviewed her about her research and upcoming talk, which is co-sponsored by the National Endowment for the Humanities, Office of Digital Humanities, as part of the partnership between NLM and NEH to collaborate on research, education, and career initiatives.
Circulating Now: Tell us a little about yourself. Where are you from? What do you do? What is your typical workday like?
Joanna Radin: I’m an Associate Professor of History of Science and Medicine, based at the Yale School of Medicine. At Yale, I teach medical students as well as undergraduate and graduate students in the School of Arts and Sciences. My research centers on the history of what I call “biomedical futures,” which you can read more about on my website or twitter account (@joannaradin). I live in Stony Creek, CT. Since COVID, my typical workday consists of hanging out with my toddler son who just learned to walk!
CN: You’ll be giving our first virtual NLM History Talk and fortuitously, your subject relates to digital technology. Tell us a little about your work in digital humanities.
JR: I’m interested in helping people to think about digital culture both historically and ethnographically. I will be especially interested to explore these questions as I, like many others, work to shift my teaching and other forms of social life online in the coming year. In this moment, as in the historical ones I document in my talk, is labor being equitably distributed? Who is being asked to perform the invisible labor and shadow work in this new digital moment?
CN: Your talk is titled “When People are Data: How Medical History Matters for Our Digital Age.” Tell us a little about the people at the center of your research.
JR: My question is: What brings people into research relationships and how do those relationships change over time. This particular talk focuses on research relationships between members of an Indigenous community in the American southwest who call themselves Akimel O’odham. This community lives on one of the oldest reservations, during which time they have developed extremely very high rates of diabetes and hypertension. Starting the 1950s, NIH-affiliated researchers set up longitudinal studies about these conditions. As it turns out, much of what we have come to know about diabetes comes from this and other similar longitudinal research projects. Unfortunately the illness Akimel O’odham and other Indigenous communities experience have not been mitigated, despite having helped biomedical researchers understand the medical conditions from which they suffer.
CN: What is the Pima Indian Diabetes Dataset (PIDD) and how did it come about?
JR: The data set emerged from the longitudinal studies conducted with Akimel O’odham (Pima is the settler name for the community). It includes eight variables associated with women of childbearing age. This data was extracted from a larger set of results, and through a series of historically specific processes, wound up becoming digitized and serving as a resource for things that had nothing to do with diabetes, health, or even women. Instead, it became an important early resource for scholars in the entirely separate field of machine learning, who were looking for particular kinds of data sets to test the new kinds of algorithms they were developing.
CN: Data is fundamental to epidemiology; how can historians engage with epidemiological datasets?
JR: They should recognize that datasets carry with them theories of knowledge that historical analysis can help reveal. In other words, asking questions about how and why datasets have come to exist can be as important as learning to work with the data itself. Learning how to “read” datasets as historical objects is a critical part of ensuring that knowledge-making practices serve the people whose bodies and experiences make them possible. When we think about epidemiological datasets as a product of particular contingent circumstances we can better assess what that data can and cannot reveal.
Joanna Radin’s presentation is part of our NLM History Talks, which promote awareness and use of the National Library of Medicine and other historical collections for research, education, and public service in biomedicine, the social sciences, and the humanities. All talks are live-streamed globally, and subsequently archived, by NIH VideoCasting. Stay informed about the lecture series on Twitter at #NLMHistTalk.