About the Book
The canon of postwar American fiction has changed over the past few decades to include far more writers of color. It would appear that we are making progress—recovering marginalized voices and including those who were for far too long ignored. However, is this celebratory narrative borne out in the data?
Richard Jean So draws on big data, literary history, and close readings to offer an unprecedented analysis of racial inequality in American publishing that reveals the persistence of an extreme bias toward white authors. In fact, a defining feature of the publishing industry is its vast whiteness, which has denied nonwhite authors, especially Black writers, the coveted resources of publishing, reviews, prizes, and sales, with profound effects on the language, form, and content of the postwar novel. Rather than seeing the postwar period as the era of multiculturalism, So argues that we should understand it as the invention of a new form of racial inequality—one that continues to shape the arts and literature today.
Interweaving data analysis of large-scale patterns with a consideration of Toni Morrison’s career as an editor at Random House and readings of individual works by Octavia Butler, Henry Dumas, Amy Tan, and others, So develops a form of criticism that brings together qualitative and quantitative approaches to the study of literature. A vital and provocative work for American literary studies, critical race studies, and the digital humanities, Redlining Culture shows the importance of data and computational methods for understanding and challenging racial inequality.
Moderated by Marisa Brown, Assistant Director for Programs at the John Nicholas Brown Center for Public Humanities and Cultural Heritage and Adjunct Lecturer in the Public Humanities, Brown University.
Free and open to the public. Please register to attend.
Purchase Redlining Culture: A Data History of Racial Inequality and Postwar Fiction from the Brown Bookstore
Richard Jean So ’01 is an assistant professor of English and cultural analytics at McGill University. He works at the intersection of cultural analysis and data science, using data-driven methods to study culture, both historical and contemporary, from the novel to Netflix to social media and writing platforms like Reddit and AO3. Professor So has a particular topical interest in race, power, and inequality. He is the author of Transpacific Community (Columbia University Press, 2016) and Redlining Culture: A Data History of Racial Inequality and Postwar Fiction (Columbia University Press, 2020), a data-driven study of white supremacy in post-war U.S. publishing and literature. Currently, he is working on a new book that studies the impact of social media and user generated content on how we talk about race and tell stories about race, which combines cultural criticism and data science. His work has also been featured in Critical Inquiry, PMLA, boundary 2, Representations, Modern Language Quarterly, American Literary History, American Literature, and Journal of Cultural Analytics.