I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.
– Sir Arthur Conan Doyle
My former PhD advisor is a very wise man and I owe a great deal of what I have accomplished to the formidable PhD training I had under his supervision. He shaped my thinking, enhanced my research skills by encouraging me and demanding from me to undertake empirical analyses. Even though my memorization capabilities and speed-reading skills have enabled me to master a broad variety of theoretical frameworks, my former PhD supervisor always wanted me to empirically test theories. Doing so gave me the best of both worlds (theory and empirics).
Throughout the course of my teaching, both at the undergraduate and graduate levels, I have refined my instructional skills and summarized in a few sentences what I demand from my students: I want my students’ research to be evidence-based, empirically-grounded and theoretically sound.
As Sir Arthur Conan Doyle’s quote has indicated above, it is foolish to theorize before one has data. Even though much of my comparative environmental policy work has focused in the development of better theories that allow us to understand why governments at various scales choose different policy options, I have years of training in empirical research methods, both qualitative and quantitative. I have undertaken in-depth qualitative studies (interviews and institutional ethnographies) and built massive datasets that have been explored through a variety of quantitative methods (including firm demographics and multivariate analysis).
Much as my students may think I’m too demanding, I strongly believe in providing them with a strong foundation in research methods. Even if I do not teach a methods course per se, I showcase examples of studies that have both sound theoretical grounding and robust empirical research methodologies. I think that the best long-lasting learning experience I can give any student is the self-confidence of knowing how to tackle a problem using empirical research methods.
Raul, this is a great post and an act worth recognizing. While you consciously convey this method to your students, you demonstrate its application in your day-to-day conversations, I would say. For the times I’ve spouted off, you’ve caught me on missing either evidence or a theoretical framework to my argument and I’m better for it. This definitely is not limited to your teaching, my friend. Thank you.
Well……
I think that the notion that theorization comes after data fails to account for the fact that nascent theories that structure the perception of reality will direct enterprising (and non-enterprising!) minds towards particular conceptions of what ‘data’ are valid for investigation, and what are even perceptible. If someone views the world through a Platonic or Aristotelian lens (just as broad examples) then what constitutes ‘data’ will likely be different from a phenomenologist, a psycho-analyst, an institutionalist, and so forth. We carry our theories before us as a way of clarifying the discordant nature of the world, and the notion that data rushes at us pre-theorization is questionable, at best. This was, of course, a key element of the Kantian and post-Kantian scientific projects.
Perhaps what you mean to say is this: we approach the world with particular perceptions that are informed by theories of being in the world, and that subsequent theorizations ought to square with those pre-existing theorizations. This said, there must be a recognition that the pre-existing theories of reality are flawed, and that sometimes an attempt to reimagine the paradigmatic understanding of the world we operate in is required (not optional, but sometimes *required* to account for reality as such) …and this will often lead to the scrapping of ‘old’ theories that a priori assumed that the previous conception of the world as such was accurate/true.
In essence, I’m trying to soften your statement, recognize that knowledge is always contingent, flawed (insofar as it never attains capital T truth value, and is instead constrained to little t truth), maleable, and has its origins in particular (as opposed to holistic) ways of understanding. Scientific inquiry is delightfully flawed, scientific processes are often started by curiosity alone that are subsequently followed up by persistent analysis and investigation into those early processes, and playfulness that operates outside of the scientific method needs to be accepted and celebrated instead of dismissed on the grounds of it failing to meet often unnecessary narrowing strictures (e.g. all should be evidence-based, etc etc.).