49 Pages Posted: 30 Apr 2010 Last revised: 2 Apr 2015
Date Written: November 22, 2010
This Article provides the first in-depth reading of the Genetic Information Nondiscrimination Act (GINA) as an antidiscrimination statute. GINA, touted as the first major civil rights legislation of the new century, passed in May 2008. Thus, both to understand GINA’s potential impact, as well as to improve its efficacy, the statute must be analyzed as an antidiscrimination law. When read as an antidiscrimination statute, GINA takes a clear position on one of the most contested issues in that area of law: antisubordination versus anticlassification. This debate queries whether antidiscrimination law should seek to elevate the social status of certain subordinated groups or should prevent all consideration of particular forbidden characteristics. GINA as currently drafted plainly favors anticlassification; it protects individuals from any intentional differential treatment by health insurers or employers based on genetic information. In contrast, an antisubordination approach to protecting genetic information would focus not on outlawing all forms of intentional, differential treatment, but on preventing a genetic underclass from forming. In particular, an antisubordination framework would allow employers to consider genetic information for accommodation purposes and victims of discrimination to challenge to facially neutral policies that produce discriminatory results. This Article proposes that amending GINA to include more antisubordination protections would better safeguard genetic information.
Keywords: Genetic Information Nondiscrimination Act, Genes, Genetic Information, Discrimination, Antisubordination, Anticlassification, Health Insurance, Employment, Antidiscrimination Theory
JEL Classification: J70, J71, J79, K10, K19, K31, K32
Suggested Citation: Suggested Citation
Roberts, Jessica L., The Genetic Information Nondiscrimination Act as an Antidiscrimination Law (November 22, 2010). Notre Dame Law Review, Vol. 86, 2010. Available at SSRN: https://ssrn.com/abstract=1597695