“Interdisciplinarity”: inter-discipline. Combining perspectives from multiple domains and approaches to research. Disciplines: bodies of research and knowledge that over the decades have developed into relative silos. What’s the difference between sociology and geography? It is primarily historic trajectory and commonly accepted approaches to knowledge production. And different academic conferences, of course.
In the 2015 academy, adding “interdisciplinary” to any sort of application goes a long way. Grant and funding agencies are actively working to dismantle the silos that structure academic knowledge production. If you as a researcher are able to show that your research team will involve humanists and social scientists, your research will stand out from the stack of applications on each committee’s desk. De-siloing the university is hot business right now. On the other hand, perhaps agencies look to fund such projects because they assume that disparate disciplines can contribute productive and complementary perspectives to the same problem or data. Perhaps they assume that single-disciplinary perspectives limit the depth of insights that can be garnered in a project. These assumptions would imply by extension that single disciplines are stale and less able to generate interesting and relevant insights into data and problems. Each of these assumptions and their implications are clearly open to critique.
One of the strengths of the Data Science for Social Good program is that it collects students from departments across the university. This combines diverse skills that are taught differently and applied to different problem sets. By “skills” I mean both software/technology packages and methods for approaching questions about the world. In our group, which looks at the relationship between social media and community well-being, we have an economist, a statistician, an applied mathematician, a social psychologist, and a geographer. We have social scientists and methodologists; qualitative and quantitative researchers; an undergraduate, grad students, and a PhD. In short, we each bring to the table a set of knowledge, skills, and thought processes that diverge from others’ along multiple axes. I don’t think this means, necessarily, that our research outcomes will be “better” than if we were all, say, statisticians; but, we are able to contribute conceptual insights from our backgrounds that speaks to other group members’ questions. For example, our group relies heavily on each other, and we consult with each other constantly throughout every day - Jordan is a scripting wizard, Jenny kills at the quantitative analysis package R, Yue is becoming a master at exploring Census and crime data, and Ryan (that’s me) provides a spatial perspective to data/problems.
However, our interdisciplinary group harbors a plethora of views on what the world is and how we can know it. That is, we have come here to the DSSG program with radically different ontologies and epistemologies. In contrast with geographers’ truism that geography is about space, it has always seemed to me to be much more fundamental than that: it’s not just adding “in space” to the end of sentences but about seeing spatial relations as the condition for - and conditioning force of - social and political processes and relations.
This is where interdisciplinarity gets tricky. For geographers (and, no doubt, other social scientists - if not researchers writ large), terms like “neighborhood”, “community”, and “well-being” are not self-explanatory terms but are themselves concepts that research should elaborate upon (see my last blog post). That is, research deepens our understanding of what a “community” is or can be. To reach this goal, different disciplines promote a variety of starting points. My conception borrows from a different set of literatures and intellectual heritage than someone in another field (with lots of overlap at times, of course). Further, in my dissertation I used the “extended case method” (check out [Burawoy’s] (http://burawoy.berkeley.edu/) work to see what that means), which, in parallels with lots of geographic work, seeks first and foremost to extend existing theoretical frameworks. Just like the enterprise of science, geographical research contributes to existing conversations, and thus does not work in a “vacuum”. Researchers don’t simply pose random new questions, but ask questions that will directly extend knowledge of a phenomenon/process.
Interdisciplinarity became a challenge during this week’s DSSG work, when we decided to conduct a literature review of some terms we use often: “neighborhood”, “well-being”, “social media”, etc. Although it’s already week 4, this is something we still haven’t done. We gathered around the table to discuss which questions we need to answer, and what methods we should use to answer those questions. Before we could even get to the second part of that sentence, we spent a great amount of time deliberating which questions we are answering. And before we could list out those questions, we spent a great deal of time wondering how many of our curiosities have already been answered in existing research. In essence, we realized we had been thinking backwards. Our backtracking caused more confusion than clarity, so I suggested we conduct a literature review to see which research topics/questions other researchers had deemed important for the field - in other words, we could identify the place where others have said we can start. Of course, the question then arose: how are we going to compare/summarize the state of the literature in economics with that of geography, with that of statistics, with that of applied math and social psychology , with that of social media. (In practice, research write-ups never borrow from a single body of literature, so this confusion is a bit of a red herring, but I hope the point about interdisciplinarity comes through.)
In the end, we decided on some questions that we are interested in answering, and will use to guide the literature review. Essentially, we want to know if and how others have addressed aspects of our problem. The questions: (1) How have “neighborhoods”, “communities”, and “community well-being” been conceived in different literatures? (2) How has technology writ large been used to improve community well-being? And most importantly, our primary contribution will be directed toward: (3) How can social media specifically be used to help improve community well-being? Even in the early stages of the literature review, it’s clear that #3 already has a few data points from research, and our study can contribute to that conversation.