Designing Better Access to Education? Unified Enrollment, School Choice, and the Limits of Algorithmic Fairness in New Orleans School Admissions

Economic sociologists have long recognized that markets have moral dimensions, but we know less about how everyday moral categories like fairness are reconciled with competing market principles like efficiency, especially in novel settings combining market design and algorithmic technologies. Here we explore this tension in the context of education, examining the use of algorithms alongside school choice policies. In US urban school districts, market design economists and computer scientists have applied matching algorithms to build unified enrollment (UE) systems. Despite promising to make school choice both fair and efficient, these algorithms have become contested. Why is it that algorithmic technologies intended to simplify enrollment and create a fairer application process can instead contribute to the perception they are reproducing inequality? Analyzing narratives about the UE system in New Orleans, Louisiana, USA, we show that experts designing and implementing algorithm-based enrollment understand fairness differently from the education activists and families who use and question these systems. Whereas the former interpret fairness in narrow, procedural, and ahistorical terms, the latter tend to evaluate fairness with consequentialist reasoning, using broader conceptions of justice rooted in addressing socioeconomic and racial inequality in Louisiana, and unfulfilled promises of universal access to quality schools. Considering the diffusion of “economic styles of reasoning” across local public education bureaucracies, we reveal how school choice algorithms risk becoming imbued with incommensurable meanings about fairness and justice, compromising public trust and legitimacy. The study is based on thirty interviews with key stakeholders in the school district’s education policy field, government documents, and local media sources.