Expelled Students in Need of Special Education Services Using Bayes’ Theorem: Implications for the Social Maladjustment Clause?

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
L. Barnard‐Brak, T. Stevens, A. Kearley
{"title":"Expelled Students in Need of Special Education Services Using Bayes’ Theorem: Implications for the Social Maladjustment Clause?","authors":"L. Barnard‐Brak, T. Stevens, A. Kearley","doi":"10.1177/01987429231160282","DOIUrl":null,"url":null,"abstract":"The purpose of the current study was to determine the probability that a student with a disability not being served by Individuals with Disabilities Education Act (IDEA) would be expelled. Expulsion data were obtained from the Civil Rights Data Collection produced by the U.S. Office of Civil Rights. The latest data from all 50 states and the District of Columbia for the 2017 to 2018 school year were analyzed. Bayes’ Theorem was used to determine this probability based upon existing probabilities and conditional probabilities. Analyses were also conducted by state and ethnicity. Results indicated that 1 in 14 of expelled students is likely to have an unserved disability under IDEA but variability according to race/ethnicity nationwide and by state was observed. Students who were White were the least likely to be an unserved student with a disability under IDEA among those expelled. The findings encourage investigation into the intersection of variables, especially the importance of including disability status and ethnicity when explaining disparate and punitive discipline. Practitioners, especially school psychologists, work at this intersection and can influence both special education identification and discipline practices.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/01987429231160282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

Abstract

The purpose of the current study was to determine the probability that a student with a disability not being served by Individuals with Disabilities Education Act (IDEA) would be expelled. Expulsion data were obtained from the Civil Rights Data Collection produced by the U.S. Office of Civil Rights. The latest data from all 50 states and the District of Columbia for the 2017 to 2018 school year were analyzed. Bayes’ Theorem was used to determine this probability based upon existing probabilities and conditional probabilities. Analyses were also conducted by state and ethnicity. Results indicated that 1 in 14 of expelled students is likely to have an unserved disability under IDEA but variability according to race/ethnicity nationwide and by state was observed. Students who were White were the least likely to be an unserved student with a disability under IDEA among those expelled. The findings encourage investigation into the intersection of variables, especially the importance of including disability status and ethnicity when explaining disparate and punitive discipline. Practitioners, especially school psychologists, work at this intersection and can influence both special education identification and discipline practices.
用贝叶斯定理驱逐需要特殊教育服务的学生:对社会失调条款的启示?
本研究的目的是确定未接受《残疾人教育法》(IDEA)服务的残疾学生被开除的可能性。驱逐数据来自美国民权办公室编制的民权数据收集。分析了2017至2018学年来自所有50个州和哥伦比亚特区的最新数据。贝叶斯定理用于根据现有概率和条件概率来确定这种概率。还按州和种族进行了分析。结果表明,根据IDEA,每14名被开除的学生中就有1人可能有未得到服务的残疾,但在全国范围内和各州都存在种族/民族差异。在被开除的学生中,白人学生最不可能成为IDEA规定的残疾学生。这些发现鼓励调查变量的交叉点,特别是在解释不同的惩罚性纪律时,包括残疾状况和种族的重要性。从业者,尤其是学校心理学家,在这个交叉点上工作,可以影响特殊教育的识别和学科实践。
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 求助全文
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
×
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