| Disproportionality and learning disabilities: parsing apart race, socioeconomic status, and language. | |
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MedLine Citation:
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PMID: 20587753 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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The disproportionate identification of learning disabilities among certain sociodemographic subgroups, typically groups that are already disadvantaged, is perceived as a persistent problem within the education system. The academic and social experiences of students who are misidentified with a learning disability may be severely restricted, whereas students with a learning disability who are never identified are less likely to receive the accommodations and modifications necessary to learn at their maximum potential. The authors use the Education Longitudinal Study of 2002 to describe national patterns in learning disability identification. Results indicate that sociodemographic characteristics are predictive of identification with a learning disability. Although some conventional areas of disproportionality are confirmed (males and language minorities), differences in socioeconomic status entirely account for African American and Hispanic disproportionality. The discrepancy between the results of bivariate and multivariate analyses confirms the importance of employing multivariate multilevel models in the investigation of disproportionality. |
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Authors:
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Dara Shifrer; Chandra Muller; Rebecca Callahan |
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Publication Detail:
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Type: Journal Article Date: 2010-06-29 |
Journal Detail:
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Title: Journal of learning disabilities Volume: 44 ISSN: 1538-4780 ISO Abbreviation: J Learn Disabil Publication Date: 2011 May-Jun |
Date Detail:
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Created Date: 2011-04-27 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0157312 Medline TA: J Learn Disabil Country: United States |
Other Details:
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Languages: eng Pagination: 246-57 Citation Subset: IM |
Affiliation:
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University of Texas at Austin, Austin, TX, USA, dshifrer@prc.utexas.edu. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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