Digital Commons Network^™

Original Discrimination: How The Supreme Court Disadvantages Plaintiff States, Heather Elliott

Articles

The U.S. Supreme Court is famously the nation's top appellate court, but Article III also makes the Court a trial court, giving it original jurisdiction over several categories of cases. One of those categories suits by states against other states-remains exclusive. Thus, when Texas sought to overturn the 202o presidential election by suing four swing states, it had only one court in which to sue. The Court properly rebuffed Texas's claim for lack of standing, but the Justices give even meritorious claims by state plaintiffs short shrift. They have made clear that these suits detract from the Court's appellate role …

What Is Consumer Protection For?, Luke Herrine

Articles

When law and economics barreled its way into consumer protection scholarship two score years ago, it brought with it the consumer sovereignty framework: an approach to analysis in which actual markets are compared to an ideal market in which consumers optimize exogenous welfare functions by choosing between optimally competitive sellers. Even after two decades of behavioralist critique and even with increasingly critical perspectives taking root since the Global Financial Crisis, this consumer sovereignty ideal continues to serve as both a descriptive and normative baseline for consumer protection scholarship.

This Article argues that it is time to reconsider the consumer sovereignty …

Assessing Amateurism In College Sports, Casey E. Faucon

Articles

College sports generate approximately $8 billion each year for the National C[artel] Athletic Association and its member institutions. Most of this revenue flows from lucrative television broadcasting deals, which often incorporate the right to commercialize and sell the names, images, and likenesses of college athletes. Under its current revenue scheme, student-athletes-85 percent of whom live below the poverty line-receive a share of zero. For over a century, we've justified this exploitative distribution scheme under a cloak of student-athlete "amateurism." Antitrust challenges to the NCAA's amateurism rules clash with the assumption that "amateurism" is a revered tradition and an important tenet …

Noncitizen Harboring And The Freedom Of Association, Shalini Bhargava Ray

Articles

No abstract provided.

Alienating Criminal Procedure, Amy F. Kimpel

Articles

No abstract provided.

On The Importance Of Being Earnest: Contrasting The Dangers Of Makeweights With The Virtues Of Judicial Candor In Constitutional Adjudication, Ronald Jr. Krotoszynski

Articles

No abstract provided.

The Surprising Virtues Of Data Loyalty, Woodrow Hartzog, Neil M. Richards

Faculty Scholarship

Lawmakers in the United States and Europe are seriously considering imposing duties of data loyalty that implement ideas from privacy law scholarship, but critics claim such duties are unnecessary, unworkable, overly individualistic, and indeterminately vague. This paper takes those criticisms seriously, and its analysis of them reveals that duties of data loyalty have surprising virtues. Loyalty, it turns out, can support collective well-being by embracing privacy’s relational turn; it can be a powerful state of mind for reenergizing privacy reform; it prioritizes human values rather than potentially empty formalism; and it offers solutions that are flexible and clear rather than …

Of Afrofuturism, Of Algorithms, Ngozi Okidegbe

Faculty Scholarship

Algorithms are proliferating in criminal legal structures. The predictions produced by these algorithms inform life-altering decisions around surveillance and incarceration. Their continued use poses a challenge to ongoing racial justice efforts. Contesting how algorithms of today maintain the racial status quo requires a fundamental rethinking of the algorithm project. This essay explores how Afrofuturism can facilitate such a rethinking. It imagines how applying an Afrofuturist paradigm to the adoption, construction, implementation, and oversight of algorithms could radically change the kind of algorithms developed and the purposes for which they are developed. Tapping into this potential offers the chance for members …

Legislating Data Loyalty, Woodrow Hartzog, Neil Richards

Faculty Scholarship

Lawmakers looking to embolden privacy law have begun to consider imposing duties of loyalty on organizations trusted with people’s data and online experiences. The idea behind loyalty is simple: organizations should not process data or design technologies that conflict with the best interests of trusting parties. But the logistics and implementation of data loyalty need to be developed if the concept is going to be capable of moving privacy law beyond its “notice and consent” roots to confront people’s vulnerabilities in their relationship with powerful data collectors.

In this short Essay, we propose a model for legislating data loyalty. Our …

#Fintok And Financial Regulation, Nikita Aggarwal, D. Bondy Valdovinos Kaye, Christopher K. Odinet

Faculty Scholarship

Social media platforms are becoming an increasingly important site for consumer finance. This phenomenon is referred to as “FinTok,” a reference to the “#fintok” hashtag that identifies financial content on TikTok, a popular social media platform. This Essay examines the new methodological possibilities for consumer financial regulation due to FinTok. It argues that FinTok content offers a novel and valuable source of data for identifying emerging fintech trends and associated consumer risks. As such, financial regulators should use FinTok content analysis—and social media content analysis more broadly—as an additional method for the supervision and regulation of consumer financial markets. The …

Securitizing Notes Of Small Businesses And Needy Workers, Tamar Frankel

Faculty Scholarship

Businesses, whether large ones or small ones, such as restaurants and small shops, are presently closed and some of their employees have been laid off.¹ Currently, the government is lending money to these small businesses² and the now unemployed workers for their sustenance. It then collects the payments from some of the borrowers and the source of the rest of the money is taxes.³ Since not all, or perhaps only a few, small businesses own real estate, they might sign notes promising to repay the loans but can offer no asset backing. Presumably, the nation’s financial deficit …

Originalism And Personal Jurisdiction: Several Questions And A Few Answers, Lawrence B. Solum, Max Crema

Faculty Scholarship

The modern constitutional law of personal jurisdiction is largely the product of living constitutionalism. International Shoe's minimum-contacts and fairness standard was not derived from the constitutional text, and it cannot be supported by the original meaning of the Due Process of Law Clauses of the Fifth and Fourteenth Amendments. This Article explores the implications of that fact for the constitutional law of personal jurisdiction, with a focus on the federal courts.

The Article proceeds in six steps. First, it lays out the theoretical framework provided by Public Meaning Originalism, including the Fixation Thesis, the Constraint Principle, and the interpretation-construction …

A Computationally Efficient Framework For Vector Representation Of Persistence Diagrams, Kit C. Chan, Umar Islambekov, Alexey Luchinsky, Rebecca Sanders

Mathematical and Statistical Science Faculty Research and Publications

In Topological Data Analysis, a common way of quantifying the shape of data is to use a persistence diagram (PD). PDs are multisets of points in R² computed using tools of algebraic topology. However, this multi-set structure limits the utility of PDs in applications. Therefore, in recent years efforts have been directed towards extracting informative and efficient summaries from PDs to broaden the scope of their use for machine learning tasks. We propose a computationally efficient framework to convert a PD into a vector in Rⁿ, called a vectorized persistence block (VPB). We show that our representation …

Optimizing Model Observer Performance In Learning-Based Ct Reconstruction, Gregory Ongie, Emil Y. Sidky, Ingrid S. Reiser, Xiaochuan Pan

Mathematical and Statistical Science Faculty Research and Publications

Deep neural networks used for reconstructing sparse-view CT data are typically trained by minimizing a pixel- wise mean-squared error or similar loss function over a set of training images. However, networks trained with such losses are prone to wipe out small, low-contrast features that are critical for screening and diagnosis. To remedy this issue, we introduce a novel training loss inspired by the model observer framework to enhance the detectability of weak signals in the reconstructions. We evaluate our approach on the reconstruction of synthetic sparse-view breast CT data, and demonstrate an improvement in signal detectability with the proposed loss.