Freitag, 7.5.2021, 15:15h

Nan Z. Da

Notre Dame

Literary Studies, Data Science, and the Future of Argumentation

This talk introduces a wider audience to the structural blind spot of the intersection of literary studies, cultural studies, and the data sciences wherein the language from respective donor disciplines is used to excuse or cover up the absence of import and rigor in the work. More than a simple disciplinary or field-specific weakness, this blind spot has real life consequences that have already taken hold of academia and its industry outputs. I go over what some of these sociological, material, and rhetorical consequences might be, and how they occur, using recent examples. With an eye towards exposition and reversal, I address the felicity and falsifiability conditions in computational/quantitative literary studies with recourse to logics from social scientific domains, and discuss similar logics from within exemplary literary studies.

Nan Z. Da is an assistant professor in the Department of English Language and Literature at the University of Notre Dame, and concurrent faculty in the Department of East Asian Languages and Cultures. She specializes in American and Chinese literature and literary histories, and comparative literary and social theory. A significant area of her research focuses on the intersection of literary studies and the data sciences, with papers published in Critical Inquiry and the Chronicle Review, as well as a large, co-piloted work-in-progress from which this talk is derived.

She is the author of Intransitive Encounter: Sino-US Literatures and the Limits of Exchange (2018), and other essays in New Literary History, Journal of Nineteenth-Century American Literature, American Literary History, Signs, and public venues such as The Yale Review, the Los Angeles Review of Books, and N+1. She is finishing a monograph called The Tragedy of Disambiguation: Chinese Diaspora and Literary Criticism.

Website: https://english.nd.edu/people/faculty/da/

Veranstaltung in englischer Sprache