Aging Barn Wood, Tom Kelly,, CC-BY-NC-ND

Generally Speaking: Reflections on Being a Generalist

“What’s your dissertation going to be about,” is perhaps the second most prominent question I’m asked, after “how are you?” It’s the graduate school version of “what’s your major?” I spent a number of years coaching myself, and then other students, about how to talk to their peers and parents about being undecided about their major. Again, I’m coaching myself on how to be a dissertation undecided.

I once told a mentor, “I’m interested in too many things.” And there is judgment associated with that phrase. I’ve always had a hard time deciding when it came to narrowing down my interests. As an academic (but really, this might apply to any young professional) I’m told to identify an area of work and dig in deep – to define myself and to build a “brand” of my scholarly work and identity. But none of the subject areas in my discipline, or honestly, anywhere, wholly describe my interests. I’ve always been more interested in the ways things connect than the ways they are minutely distinct.

Worse, even if I could define a small configuration of interests professionally, I’m abundantly curious about every other aspect of my life as well. I want to know more about everything from my emotional experience to how to fix my own car. I am, as one of my friends put it, a wannabe polyglot. And really, this is just about the worst thing you could call an academic these days.

I’ve been told that – like other academics – my interests would “mature” over time and become more specific. Five years into my graduate program, it hasn’t happened yet. It isn’t that my thinking hasn’t matured – it has. Profoundly so. But mature means more discerning, more sharp, more capable of applying a whole range of ideas, thoughts, and frameworks to the problem at hand. Mature means more capacity to hold possibilities, to play with them, to engage with

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them from various viewpoints and orientations. In short, I haven’t become a world expert in one area; it’d be better to say I’m on a path to become a master carpenter with a set of tools to bring to any task at hand.

I’ve been thinking a lot recently about my grandparents since my Nana passed away last year. My Papa (grandpa) and Nana (grandma) were exactly the kind of master craftspeople I’ve been talking about. Between the two of them, they built and fixed homes and cars, fixed and made clothes, grew their own food, cooked, and raised three children who knew how to do the same. And this was probably pretty normal for their generation. You hired a plumber when you were worried the whole sewer system was going to end up in your living room and an auto shop almost never. And they didn’t even have YouTube.

My parents did a great job helping me pursue my interests. But they didn’t often pursue their own handy projects around the house, and somewhere along the way, what was once everyday knowledge in my family became a lost inheritance. And I want it back! I don’t want to be a master carpenter, but I want to know how to work with wood. I don’t want to be a Michelin-rated chef, but I want to be a great cook. I don’t want to be a Master Gardener, but I want to raise my own food.

In short, I want to recover the generalism my grandparents embodied. And when it comes to being a scholar, I intend to be a generalist as well. I know I’m succeeding as long as I can give at least three different and substantial answers to the question “what is your research about?” I’ll have failed when I’ve got an elevator pitch or a fancy and summative title.

It takes confidence and maybe even courage to be a generalist in this world, especially academia. We have to try and fail. We enter spaces of not-knowing more often than spaces of knowing. We are regularly ignorant, regularly humbled, and never the “smartest person in the room.” This essay is my reminder, a line in the sand about the kind of scholar and academic I’d like to be. And I certainly need this mantra, because the tide that pulls to be specific is pretty strong.


Cover image: Aging Barn Wood, Tom Kelly, , CC-BY-NC-ND

Data vs. Spock, JD Hancock, CC-BY,

Ethics and Data Use

On March 16, 2015, I will host a workshop in Saint Paul, Minnesota that introduces social workers to thinking about ethics and data. As with last year, I decided to make the materials for this workshop open to anyone who wants them.

I believe we do a lot more learning when we create knowledge with other people than when we are told things by a single supposed expert. Further, there isn’t a lot of writing in the arena of big data and ethics in social services. So, I decided to replicate some past experiments and ask participants do some reading and processing on their own toward the beginning of the workshop (we aren’t allowed to provide pre-workshop materials), and then to share their learning with the rest of the group. I think this will be a much better way “in” to some of the concepts in this workshop that might be difficult because much of the language will be new to social workers. So we’ll do a jigsaw. Participants will enter the room and have the sets of articles below available to them to browse. Hopefully I can convince people to choose diversely between these areas. Then we can process these ideas together.

What I wrote last August still rings true:

My hope for the workshop is to invite people into what Ilene Alexander calls being a liminal participant – someone in an in-between state, about to move in one direction or the other into new knowledge and understanding. I think many of us in Social Work and Social Services have learned to be intimidated by technology, [and especially by “data”]. It’s “too much” when there are so many other important issues to consider. Whether we like it or not, it’s moving in ways that we can’t ignore (and shouldn’t have been). For our benefit and that of those we serve, we need to get past our defenses and sense of intimidation. At least to start, to move into a space where learning is possible. I get to do a post-assessment for the workshop. I’m considering whether I can do a pre- and post-assessment that will give me clues toward threshold concepts for learning about [big data in social work]. Knowing these threshold concepts would help plan future workshops.

Without further delay, here’s the list. Several of these resources come from a phenomenal list at Santa Clara University.

What resources do you have to recommend? Any major areas you think should be here?

Highlighted Projects in Big, Linked, and Open Data


Image Credit: Data vs. Spock, JD Hancock, CC-BY