Abstract

This paper describes a class of idealized models that illuminate minimal conditions for inequity. Some such models will track the actual causal factors that generate real world inequity. Others may not. Whether or not these models do track these real-world factors is irrelevant to the epistemic role they play in showing that minimal commonplace factors are enough to generate inequity. In such cases, it is the fact that the model does not fit the world that makes it a particularly powerful argumentative tool. As I will argue, this epistemic role is a particularly important one when it comes to modeling inequity, because such models are often also aimed at interventions to stop it. Given this, it is crucial to know if we intervene on the current causes of inequity, what other, common social factors might continue to contribute to it.