Rejoinder to “Understanding our Markov Chain Significance Test”

IF 1.5 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS Statistics and Public Policy Pub Date : 2019-01-01 DOI:10.1080/2330443X.2019.1619427
Wendy K. Tam Cho, Simon Rubinstein-Salzedo
{"title":"Rejoinder to “Understanding our Markov Chain Significance Test”","authors":"Wendy K. Tam Cho, Simon Rubinstein-Salzedo","doi":"10.1080/2330443X.2019.1619427","DOIUrl":null,"url":null,"abstract":"We thank Chikina, Frieze, and Pegden for their reply to our article. We offer just a short clarification rejoinder. In particular, we would like to be clear that we are not challenging the CFP test as a partisan gerrymandering test. We also do not “cast doubt” on the CFP paper. We have clearly stated that “we take no issues with the mathematics behind the CFP theorem or its proof.” In addition, we do not “prefer” one partisan gerrymandering test over another or advocate a single test. We firmly believe that there is plenty of room for multiple partisan gerrymandering tests. In this space, one test need not be “worse” than another. At the same time, it is indisputable that whether the CFP test would constitute a legal test for partisan gerrymandering is a legal question for the courts to decide. Legal questions cannot be decided by mathematicians. Mathematicians may make proposals, but judges decide whether to accept those proposals. Our point is simply that judges must clearly understand the mathematical concepts (even if not the mathematical details) in order to make a reasoned judgment. However, when the science is unclear, we have only miscommunication, from which no one benefits.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":"6 1","pages":"54 - 54"},"PeriodicalIF":1.5000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2019.1619427","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics and Public Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2330443X.2019.1619427","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 1

Abstract

We thank Chikina, Frieze, and Pegden for their reply to our article. We offer just a short clarification rejoinder. In particular, we would like to be clear that we are not challenging the CFP test as a partisan gerrymandering test. We also do not “cast doubt” on the CFP paper. We have clearly stated that “we take no issues with the mathematics behind the CFP theorem or its proof.” In addition, we do not “prefer” one partisan gerrymandering test over another or advocate a single test. We firmly believe that there is plenty of room for multiple partisan gerrymandering tests. In this space, one test need not be “worse” than another. At the same time, it is indisputable that whether the CFP test would constitute a legal test for partisan gerrymandering is a legal question for the courts to decide. Legal questions cannot be decided by mathematicians. Mathematicians may make proposals, but judges decide whether to accept those proposals. Our point is simply that judges must clearly understand the mathematical concepts (even if not the mathematical details) in order to make a reasoned judgment. However, when the science is unclear, we have only miscommunication, from which no one benefits.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
对“理解我们的马尔可夫链显著性检验”的答复
我们感谢中国、弗里兹和佩格登对我们文章的回复。我们只是提供一个简短的澄清反驳。特别是,我们想要明确的是,我们不是在挑战CFP测试作为一个党派的不公正划分选区的测试。我们也不“怀疑”CFP报告。我们已经明确表示,“我们对CFP定理背后的数学及其证明没有任何问题。”此外,我们不“偏爱”某一党派的不公正划分选区的测试,也不提倡单一的测试。我们坚信,有足够的空间进行多党不公正的选区划分测试。在这个空间里,一个测试不一定比另一个“更糟糕”。与此同时,CFP测试是否会构成对党派不公正划分选区的法律测试,这是法院必须决定的法律问题,这是无可争辩的。法律问题不能由数学家来决定。数学家可以提出建议,但由评委决定是否接受这些建议。我们的观点很简单,法官必须清楚地理解数学概念(即使不是数学细节),以便做出合理的判断。然而,当科学不明确时,我们只有误解,没有人从中受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Statistics and Public Policy
Statistics and Public Policy SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
3.20
自引率
6.20%
发文量
13
审稿时长
32 weeks
期刊最新文献
State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction Clusters of Jail Incarcerations in US Counties: 2010-2018 Comment on ‘What protects the autonomy of the Federal Statistics Agencies? An Assessment of the Procedures in Place That Protect the Independence and Objectivity of Official Statistics” by Pierson et al. On Coping in a Non-Binary World: Rejoinder to Biedermann and Kotsoglou Commentary on “Three-Way ROCs for Forensic Decision Making” by Nicholas Scurich and Richard S. John (in: Statistics and Public Policy)
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1