| Summary: | This article deploys text mining and quantitative analysis to survey the breadth of the Asian American literary corpus and the scholarship framing it. We have built a database covering all scholarship in the MLA bibliography, Amerasia, and the Journal of Asian American Studies that studies a literary work under the rubric of Asian American. For the works and authors cited, we collected a wealth of metadata from publisher and genre to gender, ethnicity, and more. Asian Americanists have long debated the definition of Asian American literature, but we have not traced the choices of scholarly attention that have accreted over decades and hundreds of publications to shape a canon. The results here reveal the systemic effects and inequalities generated by those choices. They confirm a long-suspected bias toward contemporary literature. They reveal troubling ethnic inequalities. The literatures of Asian American ethnic groups beyond the six most studied groups receive minimal attention. Korean American literature has leaped to second most studied, resulting in a reconfigured East Asian American hegemony: Chinese, Korean, and Japanese. This was enabled by a troubling decline in studies of Filipinx American literature, once central to the field. Much Filipinx American literature is today studied outside the Asian American framework entirely. Meanwhile, the conflation of Chinese American literature with Asian American literature has intensified. The field’s rhetoric of diversification has masked persistent inequalities in our critical practices. More encouragingly, the corpus has surpassed gender equity, placing women writers at the center of the field. The work of building the Asian American corpus we would want is far from over. Data-driven methods can be powerful
allies in the self-scrutiny necessary to this work.
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