A constructionist in an objectivist world

I was having a conversation with a scientist friend today about my doctoral research and explaining how part of my dissertation would involve grounding my research in a particular theoretical stance.  He gave me a very perplexed look, which is not really a surprising reaction from someone who is not a social scientist.  I’m sure it sounds very odd to some people to think that one’s findings and data are subject to interpretation based on one’s particular theoretical bent, but I do think it makes some sense when you’re dealing with social phenomena.

Anyway, I had written a blog post for one of my first semester doctoral classes that very much addresses this topic, so I’ve decided to repost it here.  This blog was a response to one of our class readings, so it makes some assumptions about shared vocabulary – in case you’re not familiar, here are some terms you’ll need to understand this:

  • epistemology: an understanding of knowledge and how it is constructed, which informs a theoretical basis, which in turn informs research methodologies and therefore specific methods.  It’s sort of the scaffold on which knowledge is built
  • objectivism: an epistemology that suggests that meaning and knowledge exist apart from human interpretations of things.  In other words, there is one objective Truth that can be discovered.
  • constructionism: an epistemology that suggests that meaning is constructed by human interpretation, in which case there may be multiple valid ways of constructing meaning from the same observations.

So with that in mind, here we go!

As I read Crotty’s description of epistemologies in his Introduction to The Foundations of Social Research, I naturally found myself wondering which epistemological stance most closely fit my natural approach to research and knowledge. On the one hand, objectivism deeply appeals to the scientist in me. Not only that, but I also spend my days surrounded by objectivist research in my work at the NIH. In biomedical research, there’s no room for constructing meaning about research. Either a drug works or it doesn’t; a bacterium is present in the culture or it isn’t; a reaction occurs or it doesn’t. Granted, there are plenty of ways to “game the system” to ensure you get your desired answer out of your data – outcome switching and p-hacking come to mind – but by and large, the professional world I currently inhabit is pretty strictly objectivist.

Nonetheless, I think that constructionism might be a better fit epistemologically speaking when it comes to my own research. The phenomena I’m interested in are highly social – how do researchers’ communities of practice, ways of constructing knowledge, and attitudes and experiences shape the ways that they interact with data, specifically in terms of sharing and reusing data? In fact, I argue that the social factors are possibly the most important barriers to the problem of data sharing and reuse. While it’s true that some technological barriers exist in this problem, at least work is already being done to address some of those problems. On the other hand, the social issues are much harder to quantify and therefore harder to address. I think when it comes to questions like the ones I’m asking, it’s really difficult to talk about objective approaches, so I find myself feeling drawn to constructionism.

So what’s a constructionist to do in an objectivist world? I guess partly I’m trying to situate myself within my appropriate research community and figure out how to interact with other research communities that take different epistemological approaches. Biomedical researchers may not be my research “tribe” insofar as our methods and epistemologies are concerned, but I’m keenly interested in how my research will eventually be perceived by this community because I expect my work will have implications for them, such as in terms of how they train their next generation of researchers to interact with data successfully, how they incentivize sharing and reward certain types of academic labor and research work, and even how they approach their work of data gathering at a very fundamental level.

I was on a conference call at work last week with a group that is charged with evaluating usability of a data catalog. It was easy to tell which of the participants were scientists by training. They were essentially trying to brainstorm how they could come up with a randomized controlled trial and determine some sort of gold standard for data discovery that they could use to compare to the new data catalog. It was obvious from the discussion that they were uncomfortable with the thought of employing what they considered “non-scientific” methods and skeptical about what kind of meaningful results could arise from qualitative approaches. They wanted hard, numeric data, and other types of evidence were not part of their approach.

Moving forward, I will be interested in seeing how I can reconcile the qualitative methods I may take and the constructionist approach I may adopt with the objectivist epistemologies commonly adopted with the biomedical research community.

Some real talk from a very tired PhD student

This post is going to be different from what I normally write.  It’s going to seem a little bleak for awhile, but stick with me, because it’s going to have a happy ending.

You know the way that some girls dream of their wedding day for their whole lives? That’s kind of like me, but instead of with getting married, it was with getting my PhD (I know, I was a weird kid). Starting almost 15 years ago when I was an adjunct professor, and to this day, people will sometimes send me emails that begin “Dear Dr. Federer,” and I think, not yet, but one day.

Eventually that day did come, and I got into this PhD program, working on a topic I’m really fascinated by and I think is pretty timely and relevant.  It was great.  There was the one little catch that I also had a full-time job that I love and a lease on an apartment that was well beyond grad student means, but I’m a pretty motivated person and I figured I could handle working full-time and doing the PhD program part-time.

This plan went fine the first semester.  So fine that I figured, well, why not just go ahead and do a third class in the spring?  Being a full-time PhD student with a high-pressure, full-time job?  Sure!  WHY NOT.  The semester is halfway through now, and I’m not dead yet. So this weekend, when I was looking at the PhD student handbook and I realized that after this semester, I’ll need just 4 more classes to complete my coursework, a cockamamie plan popped into my head.  I had this little conversation with myself:

evil Lisa: what if you did all four classes over the summer?
regular Lisa: I don’t know, while working full-time? That sounds like a bit much.
evil Lisa: but then once you’re done you could advance to candidacy.  Maybe you could finish the whole thing in two years!  I bet no one has ever even done that!
regular Lisa: but this sounds like torture
evil Lisa: why don’t you at least check the summer schedule and see if there are any interesting courses?regular Lisa: hmm, well, some of these do look pretty good.  And they’re online.  Maybe it wouldn’t be so bad.

And I did.

To my credit, a part of me knew this plan was not my greatest idea, so today, when I had a meeting with a potential new advisor, since my advisor is leaving for a new position, I said, “I had this idea, but I think it might be a little crazy,” and I told her and she looked at me very patiently, the way you look at a person who has lost all touch with reality and said, “yes, that’s crazy.”

After that conversation, I came back to the graduate student lounge to wait for my class to start, and I looked at the draft of a paper I’m working on, I looked at my slides for a presentation I’m giving in class this afternoon, I looked at my Outlook calendar for work, and I hated all of it.  The presentation looked like garbage and the paper seemed to be going nowhere.  I’d spent hours working on this paper, and it really had seemed like an interesting idea at the time, but now it seemed like a completely pointless waste of time.  The more I thought about data sharing and reuse, the more I hated it.

How could this be?  I love data!  I could talk about data all day!  How could it be that I suddenly hated data?  That was when I realized that I’ve been going about this all wrong and my ridiculous approach was actually ruining the entire experience.  It’s like if you love ice cream and you have a gallon and you try to jut devour the entire thing in one sitting.  Of course it would be a horrible experience.  You’d be sick and you’d hate yourself, and you’d definitely hate ice cream.  On the other hand, if you had a little bit of the ice cream over several days, you’d enjoy it a lot more.

I have this instinct from my days of long-distance running: when I’m many miles in and tired, and I want to slow down, that’s when I push myself to run even faster.  The slower I run, the longer it’ll take me to finish, but if I just run as hard as I can, the run will be over sooner.  I’m not sure about the validity of this approach from a distance running perspective, but I think it’s fair to say it’s a completely stupid idea when it comes to a PhD.

People warned me when I started this program that everyone gets burned out at some point, and I thought, not me, I love my topic, there’s no way I could ever get tired of it.  That’s why it was especially confusing when I sat there looking at my paper draft yesterday and just hating the guts out of data sharing and reuse.  Fortunately, I don’t hate data.  I hate torturing myself.

So, that’s why I’m not going to!  Could I take four courses over the summer?  I suppose.  Could I finish a PhD in two years while working full-time? I guess it’s possible.  But what would be the point, if I emerged from the process angry and tired and hating data?  Time to slow down and enjoy the ride, and de-register for at least two of those summer classes.