Reflections on Mapping Project, Part Two:
Having roughly finished the first stage of this project (data collection), I’ve had a number of observations…
My first observation has to do with the kind of reading I’ve been engaging in for this project. The close reading I do as a literary scholar is about complicating and ambiguity in a good way: taking words on the page, with implications that seem obvious, and looking for what’s not on the surface. Taking a literary text and harvesting data from it required a different way of thinking about literary information. I spent a lot of time thinking and re-thinking metadata categories, refining them, breaking them down further. I wondered what can and can’t be quantified, like taste. I spent much more time listing and categorizing than I may have ever done while working on literature. It’s been tedious at times, but a useful exercise (I’m considering having students break down motifs in a poem into a spreadsheet now, just bc it prevents us from willfully ignoring details that we don’t know how to deal with). I also found a little bit of joy when I was able to tie the text to fact: when I found that the hotels Wharton described still exist (and could be located via coordinates) or the street address for the Boston club where Archer passes the time. Or that I could make a good guess where Archer is sitting in the final scene, as he watches the sun set over the dome of Mansart in Paris. I am a contextual close reader, but I found that working toward visualization allowed me to visualize the text—personally, emotionally–in some ways that I never have before. This gave me a sense of engagement with the text AND empowerment over the material (the technical aspect of the work) that felt new. (For a great discussion of close, distant, and hyperreading, see Katherine Hayles, How We Think.)
On a more practical note, I’m starting to understand the importance of keying the tool to the project. I only knew about one approach to mapping before I came here. But now, I’ve realized that much like literary theory (in itself, a tool)—you don’t want just one. All these different mapping programs apply different approaches to the problem, and will yield different results. Another big lesson: be persistent. I stuck with OpenRefine until I got it, if in a rudimentary way. Oh, and the Mac! I thought I would have a hard time adjusting and didn’t. It feels like something that does something for you and less like a small typewriter. That’s probably because I’m asking it to do very different things than I usually ask of my PC.
Re the nature of the work, I’m struck by the importance of collaboration/distribution of labor. I think I didn’t understand the term “workflow” until now. In traditional scholarship, the workflow is much clearer bc it’s individual labor that fits into an established pattern—read, write, research, rinse, repeat. Here, there are just so many more people involved, and I’m an expert in only one area. I’m so grateful for Will, Liz, and Brian—and that they have an understanding of literature and pedagogy. It’s made me think a lot about the division of labor as a concept—how much do I need to know about the “other side”—the technicalities of tool choices, hacking my data, mapping, writing code—in order to produce a good final product? At the moment, being basically cogent feels like enough. Is this is a place in which a clear division of labor benefits? That’s a challenge for humanists, I think—we’re all used to flying solo. (And in my editorial work, my experience in production is a huge benefit; but here, the spheres are too different; there’s just too much to leapfrog over. I think I’m starting to get that real interdisciplinarity—as opposed to lit people dipping into history or psychonanalysis or whatever—requires collaboration.)
ISome larger goals as I move forward: pre-committing to the process of trial and error as we choose the tool and begin to hack around in it. I’m sure that I’ll be re-visiting data and clarifying goals and I know I need to do some more reading and writing to frame this appropriately. Ultimately, I hope to test with students and/or colleagues. And always, I need to make sure the “so what” is clearly in mind.