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A Critical Appraisal of the Evidence on Racial Disproportionality in Special Education.

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Title: A Critical Appraisal of the Evidence on Racial Disproportionality in Special Education.
Authors: Fish, Rachel Elizabeth (AUTHOR), Shores, Kenneth (AUTHOR), Souto Maior, João M. (AUTHOR)
Source: Exceptional Children. Jan2026, Vol. 92 Issue 2, p144-163. 20p.
Subjects: Special education, Black students, Data quality, Racial inequality, Confounding variables
Abstract: This essay provides a two-pronged critical assessment of a subset of the literature on racial disproportionality in special education: that which aims to estimate racial disparities among otherwise similar children. This body of research has shown that Black students are less likely than comparable White students to receive special education, and has been interpreted by many to mean that current policies meant to reduce Black over-representation may be exacerbating inequality. Our essay argues that this subset of research has fundamental limitations in its covariate adjustment practices and its data quality, making "under-representation" findings questionable. We argue that caution and further study are needed for an accurate understanding of the nature of racial disproportionality in special education. [ABSTRACT FROM AUTHOR]
Copyright of Exceptional Children is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: A Critical Appraisal of the Evidence on Racial Disproportionality in Special Education.
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  Data: <searchLink fieldCode="AR" term="%22Fish%2C+Rachel+Elizabeth%22">Fish, Rachel Elizabeth</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shores%2C+Kenneth%22">Shores, Kenneth</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Souto+Maior%2C+João+M%2E%22">Souto Maior, João M.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Exceptional+Children%22">Exceptional Children</searchLink>. Jan2026, Vol. 92 Issue 2, p144-163. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Special+education%22">Special education</searchLink><br /><searchLink fieldCode="DE" term="%22Black+students%22">Black students</searchLink><br /><searchLink fieldCode="DE" term="%22Data+quality%22">Data quality</searchLink><br /><searchLink fieldCode="DE" term="%22Racial+inequality%22">Racial inequality</searchLink><br /><searchLink fieldCode="DE" term="%22Confounding+variables%22">Confounding variables</searchLink>
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  Data: This essay provides a two-pronged critical assessment of a subset of the literature on racial disproportionality in special education: that which aims to estimate racial disparities among otherwise similar children. This body of research has shown that Black students are less likely than comparable White students to receive special education, and has been interpreted by many to mean that current policies meant to reduce Black over-representation may be exacerbating inequality. Our essay argues that this subset of research has fundamental limitations in its covariate adjustment practices and its data quality, making "under-representation" findings questionable. We argue that caution and further study are needed for an accurate understanding of the nature of racial disproportionality in special education. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Exceptional Children is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1177/00144029251350094
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      – Code: eng
        Text: English
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        PageCount: 20
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      – SubjectFull: Special education
        Type: general
      – SubjectFull: Black students
        Type: general
      – SubjectFull: Data quality
        Type: general
      – SubjectFull: Racial inequality
        Type: general
      – SubjectFull: Confounding variables
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      – TitleFull: A Critical Appraisal of the Evidence on Racial Disproportionality in Special Education.
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            NameFull: Fish, Rachel Elizabeth
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            NameFull: Shores, Kenneth
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              Text: Jan2026
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              Y: 2026
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