Controlled School Choice with Soft Bounds and Overlapping Types

Abstract

School choice programs are implemented to give students/parents an opportunity to choose the public school the students attend. Controlled school choice programs need to provide choices for students/parents while maintaining distributional constraints on the balance on the composition of students, typically in terms of socioeconomic status. Previous works show that setting soft-bounds, which flexibly change the priorities of students based on their types, is more appropriate than setting hard-bounds, which strictly limit the number of accepted students for each type. We consider a case where soft-bounds are imposed and one student can belong to multiple types, e.g., ``financially-distressed'' and ``minority'' types. We first show that when we apply a model that is a straightforward extension of an existing model for disjoint types, there is a chance that no stable matching exists. Thus, we propose an alternative model and an alternative stability definition, where a school has reserved seats for each type. We show that a stable matching is guaranteed to exist in this model, and develop a mechanism called Deferred Acceptance for Overlapping Types (DA-OT). The DA-OT mechanism is strategy-proof and obtains the student-optimal matching within all stable matchings. Computer simulation results illustrate that the DA-OT outperforms an artificial cap mechanism, where the number of seats for each type is fixed.

Cite

Text

Kurata et al. "Controlled School Choice with Soft Bounds and Overlapping Types." Journal of Artificial Intelligence Research, 2017. doi:10.1613/JAIR.5297

Markdown

[Kurata et al. "Controlled School Choice with Soft Bounds and Overlapping Types." Journal of Artificial Intelligence Research, 2017.](https://mlanthology.org/jair/2017/kurata2017jair-controlled/) doi:10.1613/JAIR.5297

BibTeX

@article{kurata2017jair-controlled,
  title     = {{Controlled School Choice with Soft Bounds and Overlapping Types}},
  author    = {Kurata, Ryoji and Hamada, Naoto and Iwasaki, Atsushi and Yokoo, Makoto},
  journal   = {Journal of Artificial Intelligence Research},
  year      = {2017},
  pages     = {153-184},
  doi       = {10.1613/JAIR.5297},
  volume    = {58},
  url       = {https://mlanthology.org/jair/2017/kurata2017jair-controlled/}
}