在旧金山联合学区设计多元化的学校选择

Maxwell Allman, I. Ashlagi, Irene Lo, J. Love, Katherine Mentzer, Lulabel Ruiz-Setz, Henry O'Connell
{"title":"在旧金山联合学区设计多元化的学校选择","authors":"Maxwell Allman, I. Ashlagi, Irene Lo, J. Love, Katherine Mentzer, Lulabel Ruiz-Setz, Henry O'Connell","doi":"10.1145/3490486.3538271","DOIUrl":null,"url":null,"abstract":"More than 65 years after the \"Brown v. Board of Education\" ruling that school segregation is unconstitutional, public schools across the U.S. are resegregating. In attempts to disentangle school segregation from neighborhood segregation, many cities have adopted policies for district-wide choice. However, these policies have largely not improved patterns of segregation. From 2018-2020, we worked with the San Francisco Unified School District (SFUSD) to design a new policy for student assignment system that meets the district's goals of diversity, predictability, and proximity. To develop potential policies, we used optimization techniques to augment and operationalize the district's proposal of restricting choice to zones. We compared these to approaches typically suggested by the school choice literature. Using predictive choice models developed using historical choice data, we find that appropriately-designed zones with minority reserves can achieve all the district's goals, at the expense of choice, and choice can resegregate diverse zones. A zone-based policy can decrease the percentage of racial minorities in high-poverty schools from 29% to 11%, decrease the average travel distance from 1.39 miles to 1.29 miles, and improve predictability, but reduce the percentage of students assigned to one of their top 3 programs from 80% to 59%. Existing approaches in the school choice literature can improve diversity at lesser expense to choice, and present a trade-off between diversity, proximity, distributional effects, and ease of understanding and implementation. Our work informed the design and approval of a zone-based policy for use starting the 2024-25 school year.","PeriodicalId":209859,"journal":{"name":"Proceedings of the 23rd ACM Conference on Economics and Computation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Designing School Choice for Diversity in the San Francisco Unified School District\",\"authors\":\"Maxwell Allman, I. Ashlagi, Irene Lo, J. Love, Katherine Mentzer, Lulabel Ruiz-Setz, Henry O'Connell\",\"doi\":\"10.1145/3490486.3538271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"More than 65 years after the \\\"Brown v. Board of Education\\\" ruling that school segregation is unconstitutional, public schools across the U.S. are resegregating. In attempts to disentangle school segregation from neighborhood segregation, many cities have adopted policies for district-wide choice. However, these policies have largely not improved patterns of segregation. From 2018-2020, we worked with the San Francisco Unified School District (SFUSD) to design a new policy for student assignment system that meets the district's goals of diversity, predictability, and proximity. To develop potential policies, we used optimization techniques to augment and operationalize the district's proposal of restricting choice to zones. We compared these to approaches typically suggested by the school choice literature. Using predictive choice models developed using historical choice data, we find that appropriately-designed zones with minority reserves can achieve all the district's goals, at the expense of choice, and choice can resegregate diverse zones. A zone-based policy can decrease the percentage of racial minorities in high-poverty schools from 29% to 11%, decrease the average travel distance from 1.39 miles to 1.29 miles, and improve predictability, but reduce the percentage of students assigned to one of their top 3 programs from 80% to 59%. Existing approaches in the school choice literature can improve diversity at lesser expense to choice, and present a trade-off between diversity, proximity, distributional effects, and ease of understanding and implementation. Our work informed the design and approval of a zone-based policy for use starting the 2024-25 school year.\",\"PeriodicalId\":209859,\"journal\":{\"name\":\"Proceedings of the 23rd ACM Conference on Economics and Computation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 23rd ACM Conference on Economics and Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3490486.3538271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd ACM Conference on Economics and Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3490486.3538271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

在“布朗诉教育委员会案”裁定学校种族隔离违宪65年后,美国各地的公立学校正在重新实行种族隔离。为了将学校隔离与社区隔离分离开来,许多城市都采取了学区范围内的选择政策。然而,这些政策在很大程度上并没有改善种族隔离的模式。从2018年到2020年,我们与旧金山联合学区(SFUSD)合作,为学生分配系统设计了一个新的政策,以满足该学区多样性、可预测性和邻近性的目标。为了制定潜在的政策,我们使用优化技术来增加和实施限制区域选择的区域建议。我们将这些方法与择校文献中通常建议的方法进行了比较。通过使用历史选择数据开发的预测选择模型,我们发现,以牺牲选择为代价,适当设计具有少数民族储备的区域可以实现所有区域的目标,而选择可以重新隔离不同的区域。以区域为基础的政策可以将高贫困学校中少数种族的比例从29%降低到11%,将平均旅行距离从1.39英里减少到1.29英里,并提高可预测性,但将分配到前3个项目之一的学生比例从80%降低到59%。学校选择文献中的现有方法可以在较少的选择代价下改善多样性,并在多样性、邻近性、分配效应以及易于理解和实施之间进行权衡。我们的工作为2024-25学年开始使用的基于区域的政策的设计和批准提供了信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing School Choice for Diversity in the San Francisco Unified School District
More than 65 years after the "Brown v. Board of Education" ruling that school segregation is unconstitutional, public schools across the U.S. are resegregating. In attempts to disentangle school segregation from neighborhood segregation, many cities have adopted policies for district-wide choice. However, these policies have largely not improved patterns of segregation. From 2018-2020, we worked with the San Francisco Unified School District (SFUSD) to design a new policy for student assignment system that meets the district's goals of diversity, predictability, and proximity. To develop potential policies, we used optimization techniques to augment and operationalize the district's proposal of restricting choice to zones. We compared these to approaches typically suggested by the school choice literature. Using predictive choice models developed using historical choice data, we find that appropriately-designed zones with minority reserves can achieve all the district's goals, at the expense of choice, and choice can resegregate diverse zones. A zone-based policy can decrease the percentage of racial minorities in high-poverty schools from 29% to 11%, decrease the average travel distance from 1.39 miles to 1.29 miles, and improve predictability, but reduce the percentage of students assigned to one of their top 3 programs from 80% to 59%. Existing approaches in the school choice literature can improve diversity at lesser expense to choice, and present a trade-off between diversity, proximity, distributional effects, and ease of understanding and implementation. Our work informed the design and approval of a zone-based policy for use starting the 2024-25 school year.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信