Dartmouth Events

Social policies target scarce resources through tags–categorical labels like “low-income” or “disability” that reflect moral ideas about who deserves help. In school districts, tags prioritize students who grow up in poverty (FRPL), students who have a disability (IEP), and students struggling to learn English (ELL). Despite the importance of tags, we know little about what happens inside districts that make these prioritization decisions and face claims on resources from parents of tagged students. The talk focuses on this gap. First, I use a series of natural experiments to investigate the effect of budget shocks on whom districts prioritize.  Second, since no ready-made data tracks parents and advocates’ attempts to shape districts’ prioritization decisions, I use computational text analysis to repurpose data from administrative hearings to measure these attempts. The results show that 1) rights granted to parents as part of Civil Rights-era legislation are used not to protect students from discrimination but instead to make positive claims upon school resources, 2) these "rights to school resources'' contribute to various forms of between-student inequality. Concluding, I discuss what the findings imply for the fairness of bureaucracies switching from tag-based prioritization to newer forms of machine learning-guided prioritization.