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What's the Matter with Computational Literary Studies?

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Bode, Katherine

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University of Chicago Press

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The debate about computational literary studies (CLS) is stuck. Forceful arguments are repeatedly made as to why literary studies must now—or could never—involve quantification, statistics, and algorithms (not least in this journal) with little sense of either side convincing the other of their case. Surveying this debate over the past decade, I propose that what seems a complete divergence of opinion obscures a fundamental agreement: that computation is separate from literary phenomena. For the field’s critics, this distinction makes CLS an oxymoron; for its proponents, both ways of knowing can contribute to literary studies, and there is critical potential in working across the divide. Yet the perception of a divide remains, and it prevents either effective critiques of reductive uses of computation (in literary studies and beyond) or productive engagements with computation’s constitutive effects (including for literary textuality and subjectivity). In charting this divide as it characterizes and limits apparently very different arguments, I connect claims about technology and subjectivity made in critiques and defenses of CLS to the separation of matter and meaning commonly referred to as Cartesian dualism. With both sides maintaining this arrangement, the debate about CLS is sealed off from technocultural inquiries in multiple fields (including literary studies) and from much of what matters in and as contemporary literary phenomena. The performative approaches to scientific and literary materiality I use to elucidate problems with the existing debate also help to characterize, explain the need for, and make legible where it already exists, a different—performative—CLS. Attuned to the coconstitution of computational methods and objects, with each other, and with literary subjectivities and textualities, this CLS builds on and extends existing critical paradigms to enable literary studies in the postprint era.

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