Section 1557 of the Affordable Care Act


Book Description

Section 1557 is the nondiscrimination provision of the Affordable Care Act (ACA). This brief guide explains Section 1557 in more detail and what your practice needs to do to meet the requirements of this federal law. Includes sample notices of nondiscrimination, as well as taglines translated for the top 15 languages by state.




Housing Discrimination


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Updates and Commentary on Employment Discrimination Law 2020


Book Description

Updates and Commentary on Employment Discrimination Law 2020, reviews developments in the field of employment discrimination law during the past year, with some notable developments from prior years where particularly influential. The review offers edited versions of some of the most important cases, summaries of other cases, and summaries of enacted and proposed legislation for an audience of researchers, students, and practitioners. The update is designed to quickly bring readers up to date with new developments in the field. Hot topics discussed include the continuing evolution in the law concerning arbitration, developments in methods of proof in disparate treatment cases, limitations on the reach of disparate impact claims, developments in mixed motives cases, new commentary and legislation connected with the #MeToo movement, developments connected with the gender pay gap, expansion of antidiscrimination protection to natural hair styles, developments in antidiscrimination protection of LGBTQ+ employees, and an upsurge in defenses based on claims of religious freedom.




EEOC Compliance Manual


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Housing Discrimination Law


Book Description

This treatise provides an in depth analysis of the legislative history, constitutionality, language, scope, substantive provisions, and enforcement of Title VIII of the Civil Rights Act of 1968. Recent developments in exclusionary zoning, redlining, and steering are discussed in detail in the work.




Discrimination in Labor Markets


Book Description

This volume contains revised versions of the papers presented in 1971 at the Princeton University Conference on Discrimination in Labor Markets, and the formal discussions of them. This paper is by Kenneth Arrow, winner of the Nobel Prize in Economics, who lays the theoretical foundations of the economic analysis of discrimination in labor markets. Finis Welch discusses the relationship between schooling and labor market discrimination. Orley Ashenfelter's paper presents a method for estimating the effect of an important institution—trade unionism—on the wages of black workers relative to whites. Ronald Oaxaca provides a framework for measuring the extent of discrimination against women. Finally, Phyllis Wallace examines public policy on discrimination and suggests strategies for public policy in this area. Originally published in 1974. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.




Federal Contract Compliance Manual


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Pattern Discrimination


Book Description

How do “human” prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? How do “human” prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? To answer this question, this book investigates a fundamental axiom in computer science: pattern discrimination. By imposing identity on input data, in order to filter—that is, to discriminate—signals from noise, patterns become a highly political issue. Algorithmic identity politics reinstate old forms of social segregation, such as class, race, and gender, through defaults and paradigmatic assumptions about the homophilic nature of connection. Instead of providing a more “objective” basis of decision making, machine-learning algorithms deepen bias and further inscribe inequality into media. Yet pattern discrimination is an essential part of human—and nonhuman—cognition. Bringing together media thinkers and artists from the United States and Germany, this volume asks the urgent questions: How can we discriminate without being discriminatory? How can we filter information out of data without reinserting racist, sexist, and classist beliefs? How can we queer homophilic tendencies within digital cultures?