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Eligibility Rates of Traditionally Underserved Individuals with Disabilities Revisited: A Data Mining Approach

In this study we used a data mining approach to examine factors affecting eligibility decision-making in the vocational rehabilitation process. Severity of disability was found to be the most important variable differentiating individuals who were accepted from those who were rejected for vocational...

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Bibliographic Details
Published in:Journal of applied rehabilitation counseling 2005-09, Vol.36 (3), p.3-10
Main Authors: Chan, Fong, Wong, Daniel W., Rosenthal, David A., Kundu, Madan M., Dutta, Alo
Format: Article
Language:English
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Summary:In this study we used a data mining approach to examine factors affecting eligibility decision-making in the vocational rehabilitation process. Severity of disability was found to be the most important variable differentiating individuals who were accepted from those who were rejected for vocational rehabilitation services. Individuals with severe disabilities had a significantly higher rate for acceptance (93%) than people without severe disabilities (55%). Race was found to be a slight differentiating factor in eligibility decisions. This study found that the prevalence and opportunity for racial bias is smaller when the criteria for eligibility are clearly defined as in the case of severe disability. Racial bias has a higher propensity to manifest itself when the criteria for eligibility are more ambiguous as in the case of justifying eligibility for vocational rehabilitation services of those without severe disabilities.
ISSN:0047-2220
2639-7641
DOI:10.1891/0047-2220.36.3.3