The Dedicated Docket in U.S. Immigration Courts: An Analysis of Fairness and Efficiency Properties

Problem definition: The dedicated docket was introduced by the Biden administration to reform the immigration system. It creates a separate queue for immigration proceedings where judges are supposed to issue a decision for each case within a target timeframe. The administration announced the docket with the goals of speed, accuracy, and fairness. Though the program meets its first goal, legal advocacy groups report that this comes at the expense of the last. Referring to it as a “denial of justice” (Murphy et al. 2023), they find that cases on the dedicated docket routinely fail to access legal representation and have a much lower asylum grant rate. Against this backdrop, we aim to understand the operational implication of the dedicated docket. Methodology/results: We develop a stylized queueing model wherein a policymaker (PM) routes asylees to either the regular or the dedicated docket and sets a delay target for the dedicated one. Constrained by the target, the court allocates its limited capacity to minimize the average delay. Immigration lawyers schedule their time between dockets to maximize the rate of successful asylum cases. Compared with a single docket, we show that the dedicated-docket system can Pareto improve both the speed and accuracy. However, if the PM sets its decision poorly, the system may be dominated by a single docket. Moreover, the dedicated-docket system can satisfy three natural fairness properties only if it is dominated by the single docket. Managerial implications: Our analysis can inform both policymakers and legal advocacy groups. We prove that the lack of fairness is a fundamental design flaw of the new program. Nonetheless, through delay differentiation, the program also enables a surprising efficiency gain. Policymakers and legal advocacy groups should be aware of such trade-offs: the same delay differentiation that enables greater efficiency also creates unfairness between dockets.

Funding: This work was supported through a Massachusetts Institute of Technology Social and Ethical Responsibilities of Computing seed grant.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.1023 and https://github.com/df365/Freund_ElectronicSupplements/blob/main/Docket_OnlineSupplement.pdf.