Disproportionality and learning disabilities: parsing apart race, socioeconomic status, and language.
Disproportionality and learning disabilities: parsing apart race, socioeconomic status, and language.
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DOI：
10.1177/0022219410374236
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发表时间：
2011-05
影响因子：
3
通讯作者：
Callahan R
中科院分区：
文献类型：
--
作者：
Shifrer D;Muller C;Callahan R
某些社会人口统计学亚组（通常已经处于不利地位的群体）中学习障碍的不成比例识别被视为教育系统中的持续问题。可能受到学习障碍的误解的学生的学术和社会经历可能受到严重限制，而从未确定的学习障碍的学生则不太可能接受以最大潜力学习所需的住宿和修改。我们使用2002年的教育纵向研究来描述学习障碍识别中的民族模式。结果表明，社会人口统计学特征可预测学习障碍的识别。尽管确认了一些常规的不成比例领域（男性和语言少数群体），但SES的差异完全解释了非裔美国人和西班牙裔不成比例。双变量和多变量分析结果之间的差异证实了使用多元多级模型在研究不成比例的研究中的重要性。
The disproportionate identification of learning disabilities among certain socio-demographic subgroups, typically groups who 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, while 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. We use the Education Longitudinal Study of 2002 to describe national patterns in learning disability identification. Results indicate that socio-demographic characteristics are predictive of identification with a learning disability. While some conventional areas of disproportionality are confirmed (males and language minorities), differences in SES entirely account for African-American and Hispanic disproportionality. Discrepancy between the results of bivariate and multivariate analyses confirms the importance of employing multivariate multilevel models in investigation of disproportionality.
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