As philosophers of science, we often find ourselves playing the role of an interdisciplinary facilitator: translating ideas, exposing background disagreements, and finding common ground between researchers from distinct disciplines. Our project was an exploration into using digital techniques to aid us in building bridges and identifying barriers between disciplines.
Overcoming disciplinary boundaries is especially important in studying global environmental change. The division of research into natural science and social science/humanities disciplines seems archaic, now that we recognize the total interdependence of human and non-human systems on our planet. Our project used corpus methods to examine how research from different disciplines approaches studying the nature/society interface. We assembled research about the “Anthropocene” from the geosciences, social sciences, and humanities, to look for areas of common ground. We found surprisingly little. Our results suggest that if we want significant collaboration across the natural/social science divide on studying global environmental change, it’s going to take some radical reorientation.
We learned a lot from this project, and we already have plans to apply the methods we learned to other projects: one of my RAs on this project is already using the techniques she learned working on this to a project about epidemiology. And I feel like a spreadsheet wizard now that I’ve had to learn how to process statistics on Big Data datasets. This is why I’m optimistic that the kind of radical academic reorientation that our changing world demands is possible: here we are, philosophers, borrowing liberally from disciplines like computer science and linguistics to reinvent how we do our work.
Philosophy of science has, by necessity, been a very case study driven field. Acquiring expertise in both philosophy and the fine details of a scientific research program takes serious investment, and it’s unrealistic for a researcher to do this for more than a handful of scientific programs. Machine-assisted analysis of research holds the possibility to provide a complementary tool, one which allows us to draw on a vast array of research for data, rather than just a handful of cases. I’m excited to see how this changes the way we think about how science works.
In digital scholarship, you’re often trailblazing and in exploration mode, and that lack of direction can make completing a project difficult. So, it helps to have milestones to aim for, and venues, and audiences in mind for your work. For us, a key milestone was a presentation to Utah’s Geology and Geophysics Department. Knowing that we had that deadline forced us to make progress, and knowing that we’d have an audience of geologists to listen to our work about geoscience/social science/humanities collaboration helped shape the questions we asked of our corpora. I don’t think our project would have been as successful if we hadn’t had that presentation to anchor it.
Digital scholarship in philosophy faces two significant barriers. To many philosophers, it seems too scientific. “How is this philosophy?” is a question I’ve heard way too often. Ironically, the other barrier is that digital philosophy isn’t scientific enough. We don’t have standards for how to assess statistical validity, we don’t have enough digital experts to guarantee credible peer review, and we don’t have a tradition of replicating and reproducing research. If we want digital philosophy to be more than a fad, we’ll need to create these structures.
This is why I’m optimistic that the kind of radical academic reorientation that our changing world demands is possible: here we are, philosophers, borrowing liberally from disciplines like computer science and linguistics to reinvent how we do our work.
–Carlos Santana, Spring 2020 DM Faculty Grant