Computational Literary Studies: Participant Forum Responses


Sarah Brouillette

DH is here to stay, including in the CLS variant whose errors Nan Da studies. This variant is especially prevalent in English programs, and it will continue to gain force there. Even when those departments have closed or merged with other units, people with CLS capacities will continue to find positions—though likely contractually —when others no longer can. This is not to say that DH is somehow itself the demise of the English department. The case rather is that both the relative health of DH and the general decline in literary studies—measured via enrollments, number of tenured faculty, and university heads’ dispositions toward English—arise from the same underlying factors. The pressures that English departments face are grounded in the long economic downturn and rising government deficits, deep cuts to funding for higher education, rising tuition, and a turn by university administrators toward boosting business and STEM programs. We know this. There has been a foreclosure of futurity for students who are facing graduation with significant debt burdens and who doubt that they will find stable work paying a good wage. Who can afford the luxury of closely reading five hundred pages of dense prose? Harried anxious people accustomed to working across many screens, many open tabs, with constant pings from social media, often struggle with sustained reading. Myself included. DH is a way of doing literary studies without having to engage in long periods of sustained reading, while acquiring what might feel like job skills. It doesn’t really matter how meaningful CLS labs’ findings are. As Da points out, practitioners themselves often emphasize how tentative their findings are or stress flaws in the results or the method that become the occasion for future investment and development. That is the point: investment and development. The key to DH’s relative health is that it supports certain kinds of student training and the development of technologically enhanced learning environments. One of the only ways to get large sums of grant money from the Social Sciences and Humanities Research Council of Canada (SSHRC) is to budget for equipment and for student training. Computer training is relatively easy to describe in a budget justification. Universities for their part often like DH labs because they attract these outside funders, and because grants don’t last forever, a campus doesn’t have to promise anything beyond short-term training and employment. As for the students: to be clear, those with DH skills don’t necessarily walk more easily into jobs than those without them. But DH labs, which at least in Canada need to be able to list training as a priority, offer an experience of education that has an affective appeal for many students—an appeal that universities work hard to cultivate and reinforce. This cultivation is there in the constant contrasts made between old fashioned and immersive learning, between traditional and project-based classrooms, between the dull droning lecture and the experiential . . . well, experience. (The government of Ontario has recently mandated that every student have an opportunity to experience “work-integrated learning” before graduation.) It is there also in the push to make these immersive experiences online ones, mediated by learning management systems such as Brightspace or Canvas, which store data via Amazon Web Services. Learning in universities increasingly occurs in data capturable forms. The experience of education, from level of participation to test performance, is cultivated, monitored, and tracked digitally. Students who have facility with digital technologies are, needless to say, at an advantage in this environment. Meanwhile the temptation to think that courses that include substantial digital components are more practical and professional – less merely academic – is pretty understandable, as universities are so busily cultivating and managing engagement in a context in which disengagement otherwise makes total sense. DH is simply far more compatible with all of these observable trends than many other styles of literary inquiry.

SARAH BROUILLETTE is a professor in the Department of English at Carleton University in Ottawa, Canada.


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2 responses to “Computational Literary Studies: Participant Forum Responses

  1. Pingback: Computational Literary Studies: A Critical Inquiry Online Forum | In the Moment

  2. Pingback: Is there a text in my data? (Part 1): On Counting Words « CA: Journal of Cultural Analytics

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