Empiricism Reloaded
You may think I am exaggerating, but I woke up puzzled with a thought that pops up on my mind recurrently:
How can we become epistemologically vigilant of ourselves while doing research?
Where can we find otherness in the research process?
What motivated this question, though, was not the epistemological vigilance per se but the differences between doing theoretical-driven research or data-driven research. I can relate to the fact that there is room for every type of researcher nowadays and paths to follow. The one I can easily see in myself is a constant drive for otherness and contrast, which perhaps leads me to search for empirical examples everywhere.
For a very humble researcher mind, this is quintessential in the process of writing. We find in the work of Roy Wagner (The Invention of Culture) for instance the notion that meanings and culture do not only exist “out there”; instead, they are things people do and invent in their daily lives. By seeing contrasts — THE OTHER — meanings and culture emerge as forms of explanation about our being in certain contexts.
Culture as a concept mostly emerges when we try to convey meanings about our differences as human beings. Basically, the take-home message Wagner helps us to convey is: creativity, culture, meanings and (ultimately) the very notion of identity only exists when we are able to unveil contrasts.
And what all this has to do with the other and researching?
We are not at the point anymore to use the notion of otherness to discover the other as the exotic one (as some sort of imperialist movement). There is no need to go to Trobriand Islands (a la Malinowski) anymore to discover otherness once again and again and again. Instead, I argue that otherness is needed in the process of conducting researches and that research is needed in order to produce otherness (in other words, contrasts). And that the material for otherness is a sort of empiricism reloaded.
It doesn’t matter if your research is about your neighbour, your friends or strangers. It doesn’t matter if you do it in your city or across the globe. What matters is the access to different sources of data (a.k.a. empirical foundations) that allow you to produce a methodological otherness: bits of reality that contrast your assumptions, your way of seeing things, possibly allowing for a sophisticated form of auto-vigilance.
As researchers, we look at the world and try to interpret it. Some believe we get to the noumenal world and others that we are stuck in the world of phenomenon. For true interpretivists, the phenomenon is all we can ultimately know. If the phenomenon is all we can aim for, then how would it be possible to do research without understanding the phenomenon? And, ultimately, how do we know anything about any phenomena out there?
Empirics is my answer.
And this is only because I would be too humble to believe that my own assumptions (or the ones I read in books) are enough to say anything about any phenomenon. With this, I am obviously saying that theories are not enough to build up arguments about the reality surrounding us.
Data can appear in the form of a text, video, audio, numbers, etc. And looking for it actively just shows the very humble process that is acknowledging something else than your own thoughts into a research process.
Please do not confuse this with a “big-data” kind of argument. The amount of data you get is not relevant to this argument. As long as we are able to contrast concepts with empirics, this is enough. Certainly, such idea is not different than the “ethnographic authority” (James Clifford) that says: “you know, I’ve been there, I talked to them, I know what I am saying”: a pretentiously modern and cautious idea we are more or less used to.
Regardless of your more quantitative or qualitative outlook on the world (personally I am more a mixed-methods individual), you might relate to the fact that:
- everyday life creates data
2. data builds identities;
3. identities help us to see the others in our assumptions;
4. seeking for the other helps us to reflect upon our particular view (obviously sociologically constrained), and therefore, to create better assumptions in our researches.
This loosely coupled argument is just a pretentious way of doubting ourselves and artificially build otherness in realms where others are virtually absent. It may be the case that you don’t wish to challenge yourself that much. And in this case, just don’t think about otherness. But don’t forget that data is never just data.
