Issue 4

The Fox Searchlight Signal: Why Fox Searchlight Marks the Beginning of the End for Preferential Treatment of Unpaid Internships at Nonprofits

While the Department of Labor has said that unpaid internships at charitable nonprofits are “generally permissible,” Fox Searchlight signals that charitable nonprofits can no longer rely on Fact Sheet #71 for protection. The Labor Department is only entitled to Skidmore deference for this document, and its assertion of protection in Fact Sheet #71 contains no justification for the sweeping exception that it announces. The Fact Sheet is therefore unlikely to persuade courts that the Labor Department’s stance is correct.

This Note predicts that arguments for preferential treatment of nonprofits proffered by authors such as Tucci, Bianci, and Harthill will fail in the courts. This Note stands alone in forecasting massive liability for the 40% of unpaid internships hosted by charitable nonprofits in the United States today. Once a nonprofit or an employee is covered by the Fair Labor Standards Act, the clear intent of Congress as articulated by the Court (as well as the Department of Labor in the context of the volunteer exception) is to draw exceptions to coverage as narrowly as possible. On top of these textual and precedent-based arguments, plaintiffs have strong public policy arguments that the continued existence of the exception encourages inefficiency, distorts the labor market, creates uncertainty, and privileges whites and elite institutions at the expense of racial and ethnic minorities. At the very least, interns at charitable nonprofits should no longer have to fend for themselves in a completely unregulated market. This Note recommends that charitable nonprofits curtail their unpaid internship programs and calls on the Labor Department to withdraw its unsupported guidance in Fact Sheet #71. It would be as easy as deleting a footnote.

Taking the Path Less Travelled: FOIA’s Impact on the Tension Between the D.C. Circuit and Vermont Yankee

The battle looked to be over; the smoke had all but cleared. Vermont Yankee—wherein the Supreme Court announced that the APA established the “maximum” procedural requirements for informal rulemaking—ostensibly brought the steady advance of judicial innovation and oversight in the regulatory state to a halt. Since Vermont Yankee was decided, however, the D.C. Circuit has continued the offensive and treated the case as a mere bridgehead. More specifically, the D.C. Circuit remains steadfast in its use of the pre-Vermont Yankee case Portland Cement to oblige agencies engaged in notice-and-comment rule making to abide by disclosure rules that cannot be found in the text of the APA or any other organic statute. Judge Brett Kavanaugh of the D.C. Circuit recently examined this apparent conflict and determined that Portland Cement stands on “shaky legal foundation” due to its dearth of statutory roots. Judge Kavanaugh’s assessment is not sui generis. In fact, few other seemingly inconsistent decisional lineages have sparked as much commentary on the APA. In an attempt to further pollinate the landscape of the current battleground, this Note journeys along the path laid down by Judge Kavanaugh and discovers a textually grounded alternative to Portland Cement. If the D.C. Circuit heeds Judge Kavanaugh’s advice and overturns Portland Cement, interested parties could simply file FOIA requests to obtain the information Portland Cement requires agencies to disclose. The goal of this Note is to explore and uncover the practical and legal consequences of a disclosure regime anchored in FOIA, and with any luck change the stakes of the debate.

The Failure of Liability in Modern Markets

This Article argues that the liability framework governing securities trading is unable to effectively deter and compensate harms in algorithmic markets. Theory underscores the significance of robust laws to safeguard information flows and the trading process. Without this assurance, investors internalize the costs of privately policing markets and will rationally discount the capital they invest. A detailed body of regulation seeks to ensure that markets function safely, benchmarking compliance using the three familiar standards grounding liability: (1) intent, (2) negligence, and (3) strict liability. This Article shows that this framework is ineffective in markets that rely on algorithms—or preprogrammed computerized instructions—for trading. It makes two claims. First, a basic level of error is endemic to the operation of algorithmic markets. Especially when designed to trade in fractions of a second, algorithms must be programmed in advance of trading and anticipate how markets are likely to behave. This predictive dynamic means that error and imprecision are inevitable, irrespective of constraints that liability imposes. Second, liability standards fare poorly in high-speed algorithmic markets where errors can spread rapidly across multiple exchanges and security types. Even small, “reasonable,” risk taking can give rise to outsized harms, diminishing the protection provided under the negligence standard. Strict liability also fails. With error inextricably a part of predictive, preset algorithms, liability can arise too frequently to function as an informative signal of bad behavior. Further, small errors can create large-scale losses that may be too high for any single firm to pay. Finally, punishing only intentional bad actors leaves a swath of the market unsanctioned for careless behavior. With each standard falling short, the current design of the liability framework can leave markets facing pervasive costs of mistake, manipulation and disruption. In concluding, this weakening of laws points to a need for structural solutions in automated markets. This Article explores avenues for reform to institutionalize better behavior and fill the gaps left by the law.

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