The Fair Priority Model offers a practical way to fulfill pledges to distribute vaccine fairly and equitably

This article defends the view that markets in education need to be restricted, in light of the problem posed by what I call the ‘educational arms race’. Markets in education have a tendency to distort an important balance between education’s role as a gatekeeper – its ‘screening’ function – and its role in helping children develop as part of a preparation for adult life. This tendency is not merely a contingent fact about markets: It can be traced to ways in which education is a partly positional good and how markets respond to (and stimulate) demand for positional goods over non-positional goods. The problem with arms races is that they allow markets to facilitate wider use of defection in a collective action problem. Using these claims, I argue that markets in education have a distinctive tendency to become objectionably exploitative. I conclude by applying some of my conclusions to illuminate various egalitarian claims about justice in education.

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This paper develops a perspective on big data in education, drawing on a broadly liberal conception of education's primary purpose. We focus especially on the rise of so-called learning analytics, and the associated rise of digitization, which we evaluate according to the liberal view that education should seek to cultivate individuality, and proceed partly by way of experimentation and with an emphasis on civic education. Our argument is not that the use of big data is wholly out of place in education. Indeed, it might have significant value in pursuit of certain educational aims. Nevertheless, the liberal conception shows how education is distinct from other domains in which big data is being applied, in ways that suggest that considerable caution must be exercised when they are used in educational contexts.