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Rebecca C. Morgan, Elder Law for Rural Elders, in Rural Aging: A Compendium on Elder Rights in Maine (2020)Clicking on the button will copy the full recommended citation.
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Royal C. Gardner and Max Finlayson, Ten Key Issues from The Global Wetlands Outlook for Decision Makers, 72 Marine & Freshwater Research 301 (2020)Clicking on the button will copy the full recommended citation.
We summarise the main findings of the Global Wetland Outlook (2018) about the status of wetlands, including their biota and ecosystem services, the drivers of change in wetlands, and the responses being adopted by the Ramsar Convention. The Outlook, which is the Ramsar Convention’s flagship publication, generally paints a bleak picture of wetland status. On the basis of these findings, we identify 10 key issues for decision makers to consider and recommend actions to implement so as to reverse the overall downward trends for wetlands. A switch from documenting the change in wetland biodiversity towards more emphasis on taking decisions is needed to implement effective responses and reverse the negative trends for wetlands. Although further data are needed, we contend that failure to place greater emphasis on effective responses could lead to the Convention becoming an irrelevant force for the wise use of wetlands.
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Grant Christensen and Melissa Tatum, Reading American Indian Law: Foundational Principles (Cambridge University Press, 2020)Clicking on the button will copy the full recommended citation.
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Stacey-Rae Simcox, Review of Recent Veterans Law Decisions of the Federal Circuit, 69 Am. U. L. Rev. 1343 (2020)Clicking on the button will copy the full recommended citation.
The last in-depth review of veterans law cases decided by the Federal Circuit was published by the American University Law Review in 2015. Since that time, the Federal Circuit has substantially changed procedural rules applicable to veterans cases, including authorizing the use of the class action device and clarifying the correct standard to use when challenging agency delay and inaction. In an important case with wide application to administrative law generally, the Federal Circuit addressed the issue of proper deference for agency regulations and policies. The Supreme Court granted certiorari in Kisor v. Wilkie and reaffirmed principles articulated in Auer v. Robbins and Bowles v. Seminole Rock & Sand Co., articulating a new three-step analysis. With regard to substantive developments in the area of veterans law, the Federal Circuit reversed a prior 2008 decision and provided final and effective relief for "Blue Water" Navy Veterans who have long fought for Agent Orange-related benefits. It is a remarkable time to be a veterans advocate, and we are pleased to provide this update.
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Grant Christensen et al., Tribal Court Litigation, in Recent Developments in Business and Corporate Litigation (American Bar Association, Business Law Section, 2020)Clicking on the button will copy the full recommended citation.
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Jason Bent, Is Algorithmic Affirmative Action Legal?, 108 Geo. L.J. 803–853 (2020)Clicking on the button will copy the full recommended citation.
It is now understood that machine learning algorithms can produce unintentionally biased results. For the last few years, legal scholars have been debating whether the disparate treatment or disparate impact theories available under Title VII of the Civil Rights Act are capable of protecting against algorithmic discrimination. But machine learning scholars are not waiting for the legal answer. Instead, they have been working to develop a wide variety of technological “fairness” solutions that can be used to constrain machine learning algorithms. They have discovered that simply blinding algorithms to protected characteristics like sex or race is insufficient to prevent algorithmic discrimination. Given enough data, algorithms will identify and leverage on proxies for the protected characteristics. Recognizing this, some scholars have proposed “fairness through awareness” or “algorithmic affirmative action” — actively using sensitive variables like race or sex to counteract unidentified sources of bias and achieve some mathematical measure of fairness in algorithmic decisions. But is algorithmic affirmative action legal? This article is the first to comprehensively consider that question under both Title VII and the Equal Protection clause of the Fourteenth Amendment. The article evaluates the legality of the leading fairness techniques advanced in the machine learning literature, including group fairness, individual fairness, and counterfactual fairness. The article concludes that existing affirmative action doctrine under Title VII and existing constitutional equal protection jurisprudence leave sufficient room for at least some forms of algorithmic affirmative action.
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Elizabeth Ippolito Boals, Adapting the Attorney-Client Interview for Remote Lawyering, in Remote Advocacy: A Guide to Survive and Thrive (NITA, 2020)Clicking on the button will copy the full recommended citation.
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Ellen S. Podgor, The Warren Court: A Mosaic of Decisions, 49 Stetson L. Rev. 215 (2020)Clicking on the button will copy the full recommended citation.
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Roy Balleste, Space Horizons: An Era of Hope in the Geostationary Orbit, 35 Journal of Envtl. L. and Litigation 165 (2020)Clicking on the button will copy the full recommended citation.
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Anne E. Mullins et al. (eds.), Florida Legal Research (5th ed., Legal Research Series, Carolina Academic Press, 2020)Clicking on the button will copy the full recommended citation.