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The ability to identify a firm's shareholders is essential to modern corporate governance practice. Corporate managers, activist hedge funds, shareholder-proposal sponsors, and other market actors all use this information in their efforts to shape corporate action. They can do so, however, only by dint of regulatory fiat. Since the 1970s, the US Securities and Exchange Commission (SEC) has required institutional investors to disclose their equity holdings every quarter on Form 13F. Today, these disclosures provide the best (and often the only) identifying information about a firm's shareholders. But while countless studies in law and finance rely on 13F data, none have turned the microscope around to examine the program itself. This article fills this gap by comprehensively mapping 13F’s significant impacts across a wide range of corporate governance processes. It examines numerous ways 13F shapes the corporate governance ecosystem, most of which have never previously been identified, much less closely examined. Among other findings, it shows that 13F likely mitigates the short-term bias of hedge fund activism; bolsters institutional-investor advocacy on environmental, social, and governance topics; promotes more “collaborative” engagements between shareholders and managers; drives a robust “competition for votes” ahead of key elections; and facilitates the anticompetitive effects of common ownership. There is an urgent need to understand these effects. In 2020 the SEC proposed eliminating 90% of 13F reports. Now, there are proposals pending before the Agency and Congress to expand the volume and frequency of reporting. But these proposals and the commentary surrounding them universally fail to consider 13F’s role in corporate governance. In addition to mapping 13F’s current impacts, this article also analyzes how each proposed reform would reshape this landscape. Surprisingly, I find several areas where shareholders and other corporate stakeholders could be made better off with less transparency about institutional holdings. As policymakers weigh changes to 13F, they should look past the impact on “market transparency” to consider how this information is actually being used on the ground, by whom, and to what ends.

Two developments have transformed the detection of corporate fraud in the last decade: the Securities and Exchange Commission's Whistleblower Bounty Program (WBP) and the rise of activist short sellers. The WBP offers up financial bounties to individuals who bring forward actionable information about securities fraud. Activist shorts conduct due diligence to identify overvalued public companies, take short positions, reveal the negative information, and then enjoy trading profits if and when the stock tanks. Considered separately, these institutions are widely regarded as socially valuable innovations that help deter fraud.

Allele age has long been a focus of population genetic research, primarily because it can be an important clue to the fitness effects of an allele. By virtue of their effects on fitness, alleles under directional selection are expected to be younger than neutral alleles of the same frequency. We developed a new coalescent-based estimator of a close proxy for allele age, the time when a copy of an allele first shares common ancestry with other chromosomes in a sample not carrying that allele. The estimator performs well, including for the very rarest of alleles that occur just once in a sample, with a bias that is typically negative. The estimator is mostly insensitive to population demography and to factors that can arise in population genomic pipelines, including the statistical phasing of chromosomes. Applications to 1000 Genomes Data and UK10K genome data confirm predictions that singleton alleles that alter proteins are significantly younger than those that do not, with a greater difference in the larger UK10K dataset, as expected. The 1000 Genomes populations varied markedly in their distributions for singleton allele ages, suggesting that these distributions can be used to inform models of demographic history, including recent events that are only revealed by their impacts on the ages of very rare alleles.

Although the whistleblower programs (WBPs) created by Dodd-Frank have received universal acclaim, little is known about how they actually work. In 2021, the Securities and Exchange Commission (SEC) received an average of forty-nine whistleblower tips every workday. Success depends on sifting through this avalanche of tips to determine which ones to investigate. To date, however, the tip-sifting process has been entirely shrouded in secrecy. This Article breaks new ground. It offers a rare look inside the WBPs administered by both the SEC and the Commodity Futures Trading Commission (CFTC), shining a bright light on the critical role played by private whistleblower attorneys in the tip-sifting process. Using a new dataset comprised of informationi obtained under the Freedom of Information Act, I find (among other things) that tipsters represented by lawyers appear to significantly outperform unrepresented ones, repeat-player lawyers appear to outperform first-timers, and lawyers who used to work at the SEC appear to outperform just about everybody. The upshot is that the SEC and CFTC have effectively privatized the tipsifting function at the core of the WBPs. Private lawyers have earned hundreds of millions of dollars in fees from these programs, with a disproportionate share going to a concentrated group of well-connected repeat players. Unlike traditional plaintiff-side securities attorneys and attorneys who represent clients seeking government payments in many other contexts, private whistleblower lawyers operate free from virtually all public accountability, transparency, or regulation. I highlight significant efficiency and accountability deficits imposed by this private outsourcing program and propose reforms to realign these private actors with the public interest.

Companies targeted by SEC enforcement actions often face parallel private class actions under the federal securities laws based on the same underlying conduct. But when the SEC selects enforcement targets, negotiates settlements, and assesses its own performance, it is unclear whether or how the agency considers this potential \"piggybacking\" effect. Although the agency's enforcement activities can have significant impacts on the flow of private litigation, the agency denies that it accounts for those potential impacts informulating enforcement policy. The SEC is not idiosyncratic in this respect. Its practice reflects a gap in our understanding of how public agencies channel private litigation. While scholars have analyzed various deliberate and overt forms of agency \"litigation gatekeeping,\" and have debated the social utility of \"piggyback\" litigation, the capacity and incentives of agencies to deliberately channel the flow of \"piggyback\" litigation have not been carefully examined. This paperfills that gap. I argue that agencies like the SEC should consider the potential private litigation consequences of their enforcement activities. And I propose adjustments to the enforcement regime to integrate consideration of the \"piggyback\" effect in a transparent and systematic manner. For thirty years, securities regulation scholars have proposed expanding the SEC's authority to control the flow of private securities class actions. But these proposals face significant conceptual and practical challenges and have not gained traction. This paper offers a new path forward: the SEC should make better use of its existing, inchoate authority to channel private litigation by systematically incorporating the \"piggyback\" effect into its enforcement decisionmaking.

When the Securities and Exchange Commission (SEC) files an administrative enforcement action, the respondent is ordinarily entitled to present their case orally at an in-person hearing before one of the agency's Administrative Law Judges. But, in hundreds of administrative proceedings over the past twenty-five years, the agency has skipped over this inperson hearing, instead resolving actions on motions for \"summary disposition. \" This is illegal. Most SEC administrative proceedings are governed by the Administrative Procedure Act's (APA) provisions governing \"formal\" adjudications. One of those provisions - long overlooked or misinterpreted by scholars and courts-can only be reasonably interpreted as granting respondents an absolute right to an oral hearing in cases where the agency is seeking to impose \"sanctions\" like those the SEC imposes in administrative proceedings. The 1946 Congress that enacted the APA declined to follow the trans-substantive summary judgment rule that had been recently adopted as part of the Federal Rules of Civil Procedure, and instead followed the alternative model of the many American states that permitted summary judgment only in specifically enumerated categories of cases. The legislative history and contemporaneous interpretations confirm that the APA prohibits summary process for formal adjudications leading to \"sanctions.\" Administrative summary judgment is also questionable on policy grounds. Proponents argue that administrative summary judgment promotes administrative efficiency, but have overlooked how the procedure may distort agency enforcement priorities, undermine congressional control of administrative agencies, be subject to systematic abuse by agencies, and unfairly deprive some individuals of important procedural rights. This paper provides an empirical study of SEC summary disposition from its promulgation in 1995 through 2019, examines the text and history of the APA to demonstrate the illegality of this procedure, and challenges the conventional policy justifications for the procedure.

Joy Bergelson and colleagues characterize genome-wide patterns of genetic variation in a collection of 1,307 worldwide Arabidopsis thaliana accessions from the Regional Mapping (RegMap) panel, a publicly available genomic resource that includes large regional panels. They characterize signatures of selection and patterns of recombination and identify an enrichment of hotspots in intergenic regions and in repetitive DNA. Arabidopsis thaliana is native to Eurasia and is naturalized across the world. Its ability to be easily propagated and its high phenotypic variability make it an ideal model system for functional, ecological and evolutionary genetics. To date, analyses of the natural genetic variation of A . thaliana have involved small numbers of individual plants or genetic markers. Here we genotype 1,307 worldwide accessions, including several regional samples, using a 250K SNP chip. This allowed us to produce a high-resolution description of the global pattern of genetic variation. We applied three complementary selection tests and identified new targets of selection. Further, we characterized the pattern of historical recombination in A. thaliana and observed an enrichment of hotspots in its intergenic regions and repetitive DNA, which is consistent with the pattern that is observed for humans but which is strikingly different from that observed in other plant species. We have made the seeds we used to produce this Regional Mapping (RegMap) panel publicly available. This panel comprises one of the largest genomic mapping resources currently available for global natural isolates of a non-human species.

Linkage disequilibrium (LD) is a fundamental concept in genetics; critical for studying genetic associations and molecular evolution. However, LD measurements are only reliable for common genetic variants, leaving low-frequency variants unanalyzed. In this work, we introduce cumulative LD (cLD), a stable statistic that captures the rare-variant LD between genetic regions, which reflects more biological interactions between variants, in addition to lack of recombination. We derived the theoretical variance of cLD using delta methods to demonstrate its higher stability than LD for rare variants. This property is also verified by bootstrapped simulations using real data. In application, we find cLD reveals an increased genetic association between genes in 3D chromatin interactions, a phenomenon recently reported negatively by calculating standard LD between common variants. Additionally, we show that cLD is higher between gene pairs reported in interaction databases, identifies unreported protein-protein interactions, and reveals interacting genes distinguishing case/control samples in association studies.

Modern sequencing instruments bring unprecedented opportunity to study within-host viral evolution in conjunction with viral transmissions between hosts. However, no computational simulators are available to assist the characterization of within-host dynamics. This limits our ability to interpret epidemiological predictions incorporating within-host evolution and to validate computational inference tools. To fill this need we developed Apollo, a GPU-accelerated, out-of-core tool for within-host simulation of viral evolution and infection dynamics across population, tissue, and cellular levels. Apollo is scalable to hundreds of millions of viral genomes and can handle complex demographic and population genetic models. Apollo can replicate real within-host viral evolution; accurately recapturing observed viral sequences from HIV and SARS-CoV-2 cohorts derived from initial population-genetic configurations. For practical applications, using Apollo-simulated viral genomes and transmission networks, we validated and uncovered the limitations of a widely used viral transmission inference tool. Apollo is a GPU-accelerated simulator of within-host viral evolution, spanning host populations, tissues, and cells. It scales to millions of viral genomes and supports complex demographic and population genetic models.

That population size affects the fate of new mutations arising in genomes, modulating both how frequently they arise and how efficiently natural selection is able to filter them, is well established. It is therefore clear that these distinct roles for population size that characterize different processes should affect the evolution of proteins and need to be carefully defined. Empirical evidence is consistent with a role for demography in influencing protein evolution, supporting the idea that functional constraints alone do not determine the composition of coding sequences. Given that the relationship between population size, mutant fitness and fixation probability has been well characterized, estimating fitness from observed substitutions is well within reach with well-formulated models. Molecular evolution research has, therefore, increasingly begun to leverage concepts from population genetics to quantify the selective effects associated with different classes of mutation. However, in order for this type of analysis to provide meaningful information about the intra- and inter-specific evolution of coding sequences, a clear definition of concepts of population size, what they influence, and how they are best parameterized is essential. Here, we present an overview of the many distinct concepts that “population size” and “effective population size” may refer to, what they represent for studying proteins, and how this knowledge can be harnessed to produce better specified models of protein evolution.