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Full-Text Articles in Law
Assessing The Viability Of Implicit Bias Evidence In Discrimination Cases: An Analysis Of The Most Significant Federal Cases, Anthony Kakoyannis
Assessing The Viability Of Implicit Bias Evidence In Discrimination Cases: An Analysis Of The Most Significant Federal Cases, Anthony Kakoyannis
Florida Law Review
The theory of implicit bias occupies a rapidly growing field of scientific research and legal scholarship. With the advent of tools measuring individuals’ subconscious biases toward people of other races, genders, ages, national origins, religions, and sexual orientations, scholars have rushed to explore the ways in which these biases might affect decision-making and produce broad societal consequences. The question that remains unanswered for scholars, attorneys, and judges is whether evidence of implicit bias and its effects can or should be used in legal proceedings. Although the study of implicit bias dates back several decades, only recently have judicial opinions begun …
Equality, Equity, And Dignity, Nancy E. Dowd
Equality, Equity, And Dignity, Nancy E. Dowd
UF Law Faculty Publications
In this Essay I explore the definition and scope of children’s equality. I argue that equality includes equity and dignity. The meaning of each of these concepts is critical in imagining a deep, rich vision of equality, and in constructing policies to achieve that vision. This definition of equality creates affirmative rights, demands action to resolve structural discrimination that creates and sustains hierarchies among children, and requires affirmative support for children’s developmental equality.
Antidiscriminatory Algorithms, Stephanie Bornstein
Antidiscriminatory Algorithms, Stephanie Bornstein
UF Law Faculty Publications
Can algorithms be used to advance equality goals in the workplace? A handful of legal scholars have raised concerns that the use of big data at work may lead to protected class discrimination that could fall outside the reach of current antidiscrimination law. Existing scholarship suggests that, because algorithms are “facially neutral,” they pose no problem of unequal treatment. As a result, algorithmic discrimination cannot be challenged using a disparate treatment theory of liability under Title VII of the Civil Rights Act of 1964 (Title VII). Instead, it presents a problem of unequal outcomes, subject to challenge using Title VII’s …