Volume 53, Issue 2

3 posts

#TimesUp On Individual Litigation Reform: Combatting Sexual Harassment Through Employee-Driven Action and Private Regulation

By Natalie Dugan

In 2017, the New York Times published a story that exposed severe sexual misconduct on the part of Harvey Weinstein, an American film producer. The revelation of Weinstein’s conduct proved to be a watershed moment for the public’s comprehension of sexual harassment and violence in the workplace. Movements like the #MeToo and TimesUp initiatives quickly gained substantial momentum, reflecting a newfound and widespread commitment to combatting this form of misconduct.

This Note, however, aims to illuminate the barriers to progress those movements, and others, will face in their attempts to eradicate sexual harassment and violence in the broader workplace context, beyond the scope of Hollywood. The narrow focus on overt sexual misconduct, along with a general failure to circumvent the pre-existing shortcomings of the U.S. court system in addition to the various disadvantages of pursuing individual litigation, have the potential to prevent such movements from achieving lasting change. As such, this Note offers an alternative framework for combatting sexual misconduct in the workplace, through the implementation of employee-driven groups modeled after The Fair Food Program. Moreover, this Note offers possible means through which government intervention might facilitate cooperation between corporations and said employee-driven groups.

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The Curious Case of Lawrence Hoskins: Evaluating the Scope of Agency Under the Anti-Bribery Provisions of the FCPA

By Christian R. Martinez

The Foreign Corrupt Practices Act (FCPA) explicitly defines the categories of entities subject to its provisions. One such category refers to any “agent of a domestic concern.” But what exactly is an agent of a domestic concern? In United States v. Hoskins, the Second Circuit decidedly refused to answer that question. This Note argues that, in the context of cross-border bribery, an agent of a domestic concern has a specific definition: a local third-party contracted by a non-local supplier to serve as a representative and to facilitate the movement of bribe payments between that supplier (the briber) and a local consumer (the bribee).

In making this argument, this Note underscores the significance of the Organisation for the Economic Co-operation and Development’s (OECD) Convention on Combatting Bribery of Foreign Public Officials in International Business Transactions (Anti-Bribery Convention) and its effect on FCPA enforcement. Part II provides background information to the FCPA and examines the Second Circuit’s decision in United States v. Hoskins. Part III explores the importance of the OECD Anti-Bribery Convention and juxtaposes this Note’s proposed definition of an agent of a domestic concern with traditional principles of agency. Part IV applies this Note’s proposed definition of an agent of a domestic concern to the facts of United States v. Hoskins and explains why courts should adopt this definition as well.

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Algorithmic Harms to Workers in the Platform Economy: The Case of Uber

By Zane Muller

Technological change has given rise to the much-discussed “gig” or “platform economy,” but labor law has yet to catch up. Platform firms, most prominently Uber, use machine learning algorithms processing torrents of data to power smartphone apps that promise efficiency, flexibility, and autonomy to users who both deliver and consume services. These tools give firms unprecedented information and power over their services, yet they are little-examined in legal scholarship, and case law has yet to meaningfully address them. The potential for exploitation of workers is immense, however the remedies available to workers who are harmed by algorithm design choices are as yet undeveloped.

This Note analyzes a set of economic harms to workers uniquely enabled by algorithmic work platforms and explores common law torts as a remedy, using Uber and its driver-partners as a case study. Part II places the emerging “platform economy” in the context of existing labor law. Part III analyzes the design and function of machine learning algorithms, highlighting the Uber application. This Part of the Note also examines divergent incentives between Uber and its users alongside available algorithm design choices, identifying potential economic harms to workers that would be extremely difficult for workers to detect. Part IV surveys existing proposals to protect platform workers and offers common law causes of action sounding in tort and contract as recourse for workers harmed by exploitative algorithm design.

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