A vast literary whiteness and becoming undisciplined: A review of Redlining Culture

Abstract

This review of Richard So's Redlining Culture considers the implication of algorithmic analysis to work in the humanities and its potetial for curriculum studies.  By applying advanced data science techniques and big data analytics, So examines the representation of racial characters in fiction and uncovers persistent patterns of exclusion despite claims of increasing multiculturalism. This review acknowledges the ethical concerns surrounding data-driven scholarship, emphasizing the importance of troubling the data and considering the implications of algorithmic tools in anti-racist interventions. It calls for a reevaluation of the relationships between data, cultural history, and reading, highlighting the necessity of interrogating and disrupting entangled histories to promote inclusive representations in both literature and curriculum studies.