In Response to “In Praise of Makeshift Finishing” by Daniel Tubb Writing in Puzzle-Pieces

In the summer, when workdays are flexible, I tend to block out two different kinds of time. One is for the kind of ethnographic writing that Tubb describes so eloquently. This requires concentration and flow; a re-immersion into the mental space of fieldwork, balanced with enough distance to see the big picture. The other kind is quantitative work. This means wrangling large spreadsheets of survey data, arranged according to the angular logic of statistical analysis software. Working with this kind of data takes similar concentration. During these time blocks, I feel as if I were climbing inside the dataset, like a jungle gym, to get a sense of the relationships linking one thing to another. Familiarity with individual pieces helps to visualize the whole. I find tacking back and forth across these different modes to be useful. Working with statistical analysis helps me develop more confidence about the patterns I see in qualitative data; and ethnography helps me come up with better questions to ask (or put more formally, hypotheses to test) in quantitative analysis. But what “finishing” looks like differs between these two modes of engagement. To start, the role of words diverges. In my ethnographic writing, I aim for a well-crafted piece of prose, a balance between “thick description” and economy of language. As I revise from first to final drafts, I often find that pieces get shorter as I hone the point of a story. Less, often, is more. In writing up quantitative work, the economy is in the tables. A single table of statistical analysis in a published paper might represent several weeks’ efforts. As in ethnography, what’s visible are the outcomes that were most legible, that tell the “story” most succinctly. Unseen are the approaches I tried that gave inconclusive results; or, before that, all the time spent “cleaning” data, ensuring, for example, that all columns containing numbers contain only numbers, and not text; or, before that, the time spent in the field, going door-to-door and asking the same questions, over and over, to hundreds of people. In quantitative analysis, the tables and figures congeal these many efforts, becoming the core of a paper’s argument. Here, too, less is more – but words are, very nearly, secondary. Time frames for finishing, too, are different. There is pressure to publish survey data quickly, before it gets “old.” Reviewers ask, sometimes point-blank, why quantitative results were not published sooner. This stands in contrast to ethnographic writing, where sitting with what we have learned and experienced “and letting it mellow as time unfolds” is an important part of the method. Even so, there are advantages to the quicker temporalities of quantitative write-ups. In principle, one is responsible for producing a methodologically sound and defensible statement about patterns that held true in their dataset; but this is not necessarily the definitive statement for building theory. Especially for fields far from the social sciences, like biology or medicine, each paper is a puzzle piece, to be interlocked with those produced by other studies to form a larger picture. The pressure to publish quickly is mitigated by the notion that science is a collectively produced endeavour, and results of any single study should be replicated in others before shifting theory, or clinical practice. Of course, as ethnographers of development know, the shared responsibility of collective knowledge production does not always bear out. The economy of numbers also lends them an air of certainty, liable to over-interpretation in policy spheres; and high-impact journals look for research that will make headlines, driving attention and digital traffic. These conditions present risks especially when working …