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Sorting Machines: Digital Technology and Categorical Inequality in Education

Matthew Rafalow,Cassidy Puckett

Published 2021 in Educational Research

ABSTRACT

Existing scholarship suggests that schools do the work of social stratification by functioning as “sorting machines,” or institutions that determine which populations of students are provided educational resources needed to help them get ahead. We build on this theory of social reproduction by extending it to better understand how digital technology use is implicated in this process of unequal resource allocation in schools. We contend that educational resources, like digital technologies, are also sorted by schools. Drawing on scholarship from both education research and science and technology studies, we show how educational institutions have long played a role in constructing the value of technologies to different ends, by constructing hierarchies of technological activity, like “vocational” and “academic” computer use, even when strikingly similar. We then apply this lens to three areas of inquiry in education research: the use of digital technologies for instruction, school use of student data, and college admissions. Each illustrates how education scholars can view technologies as part of school sorting processes and with implications for inequality within and beyond the classroom.

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