cssi/SciSciGPT-SciSciNet huggingface dataset:
Driving integrative structural modeling with serial capture affinity purification

Streamlined characterization of protein complexes remains a challenge for the study of protein interaction networks. Here we describe serial capture affinity purification (SCAP), in which two separate proteins are tagged with either the HaloTag or the SNAP-tag, permitting a multistep affinity enrichment of specific protein complexes. The multifunctional capabilities of this protein-tagging system also permit in vivo validation of interactions using acceptor photobleaching Forster resonance energy transfer and fluorescence cross-correlation spectroscopy quantitative imaging. By coupling SCAP to cross-linking mass spectrometry, an integrative structural model of the complex of interest can be generated. We demonstrate this approach using the Spindlin1 and SPINDOC protein complex, culminating in a structural model with two SPINDOC molecules docked on one SPIN1 molecule. In this model, SPINDOC interacts with the SPIN1 interface previously shown to bind a lysine and arginine methylated sequence of histone H3. Our approach combines serial affinity purification, live cell imaging, and cross-linking mass spectrometry to build integrative structural models of protein complexes.
Emotional health concerns of oncology physicians in the United States: Fallout during the COVID-19 pandemic.

Introduction Cancer care is significantly impacted by the Coronavirus Disease 2019 (COVID-19) pandemic. Our objective was to evaluate the early effects of the pandemic on the emotional well-being of oncology providers across the United States and explore factors associated with anxiety and depression symptoms. Materials and methods A cross-sectional survey was administered to United States cancer-care physicians recruited over a two-week period (3/27/2020–4/10/2020) using snowball-convenience sampling through social media. Symptoms of anxiety and depression were measured using the Patient Health Questionnaire (PHQ-4). Results Of 486 participants, 374 (77.0%) completed the PHQ-4: median age was 43 years; 63.2% female; all oncologic specialties were represented. The rates of anxiety and depression symptoms were 62.0% and 23.5%, respectively. Demographic factors associated with anxiety included female sex, younger age, and less time in clinical practice. Perception of inadequate personal protective equipment (68.6% vs. 57.4%, p = 0.03) and practicing in a state with more COVID-19 cases (65.8% vs. 51.1%, p = 0.01) were associated with anxiety symptoms. Factors significantly associated with both anxiety and depression included the degree to which COVID-19 has interfered with the ability to provide treatment to cancer patients and concern that patients will not receive the level of care needed for non-COVID-19 illness (all p-values <0.01). Conclusion The perceived degree of interference with clinical practice along with personal concerns about COVID-19 were significantly associated with both anxiety and depression among oncology physicians in the United States during the COVID-19 pandemic. Our findings highlight factors associated with and sources of psychological distress to be addressed to protect the well-being of oncology physicians.
SemEval-2020 Task 6: Definition Extraction from Free Text with the DEFT Corpus.

Research on definition extraction has been conducted for well over a decade, largely with significant constraints on the type of definitions considered. In this work, we present DeftEval, a SemEval shared task in which participants must extract definitions from free text using a term-definition pair corpus that reflects the complex reality of definitions in natural language. Definitions and glosses in free text often appear without explicit indicators, across sentences boundaries, or in an otherwise complex linguistic manner. DeftEval involved 3 distinct subtasks: 1) Sentence classification, 2) sequence labeling, and 3) relation extraction.
A comprehensive evaluation of long read error correction methods

Third-generation single molecule sequencing technologies can sequence long reads, which is advancing the frontiers of genomics research. However, their high error rates prohibit accurate and efficient downstream analysis. This difficulty has motivated the development of many long read error correction tools, which tackle this problem through sampling redundancy and/or leveraging accurate short reads of the same biological samples. Existing studies to asses these tools use simulated data sets, and are not sufficiently comprehensive in the range of software covered or diversity of evaluation measures used. In this paper, we present a categorization and review of long read error correction methods, and provide a comprehensive evaluation of the corresponding long read error correction tools. Leveraging recent real sequencing data, we establish benchmark data sets and set up evaluation criteria for a comparative assessment which includes quality of error correction as well as run-time and memory usage. We study how trimming and long read sequencing depth affect error correction in terms of length distribution and genome coverage post-correction, and the impact of error correction performance on an important application of long reads, genome assembly. We provide guidelines for practitioners for choosing among the available error correction tools and identify directions for future research. Despite the high error rate of long reads, the state-of-the-art correction tools can achieve high correction quality. When short reads are available, the best hybrid methods outperform non-hybrid methods in terms of correction quality and computing resource usage. When choosing tools for use, practitioners are suggested to be careful with a few correction tools that discard reads, and check the effect of error correction tools on downstream analysis. Our evaluation code is available as open-source at https://github.com/haowenz/LRECE .
Leveraging Decentralized Artificial Intelligence to Enhance Resilience of Energy Networks

This paper reintroduces the notion of resilience in the context of recent issues originated from climate change triggered events including severe hurricanes and wildfires. A recent example is PG&E’s forced power outage to contain wildfire risk which led to widespread power disruption. This paper focuses on answering two questions: who is responsible for resilience? and how to quantify the monetary value of resilience? To this end, we first provide preliminary definitions of resilience for power systems. We then investigate the role of natural hazards, especially wildfire, on power system resilience. Finally, we will propose a decentralized strategy for a resilient management system using distributed storage and demand response resources. Our proposed high fidelity model provides utilities, operators, and policymakers with a clearer picture for strategic decision making and preventive decisions.
Self-consistent effective Hamiltonian theory for fermionic many-body systems

Using a separable many-body variational wavefunction, we formulate a self-consistent effective Hamiltonian theory for fermionic many-body system. The theory is applied to the two-dimensional (2D) H...
MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing.

Named entity typing (NET) is a classification task of assigning an entity mention in the context with given semantic types. However, with the growing size and granularity of the entity types, few previous researches concern with newly emerged entity types. In this paper, we propose MZET, a novel memory augmented FNET (Fine-grained NET) model, to tackle the unseen types in a zero-shot manner. MZET incorporates character-level, word-level, and contextural-level information to learn the entity mention representation. Besides, MZET considers the semantic meaning and the hierarchical structure into the entity type representation. Finally, through the memory component which models the relationship between the entity mention and the entity type, MZET transfers the knowledge from seen entity types to the zero-shot ones. Extensive experiments on three public datasets show the superior performance obtained by MZET, which surpasses the state-of-the-art FNET neural network models with up to 8% gain in Micro-F1 and Macro-F1 score.
FACT: A Diagnostic for Group Fairness Trade-offs

Group fairness, a class of fairness notions that measure how different groups of individuals are treated differently according to their protected attributes, has been shown to conflict with one another, often with a necessary cost in loss of model's predictive performance. We propose a general diagnostic that enables systematic characterization of these trade-offs in group fairness. We observe that the majority of group fairness notions can be expressed via the fairness-confusion tensor, which is the confusion matrix split according to the protected attribute values. We frame several optimization problems that directly optimize both accuracy and fairness objectives over the elements of this tensor, which yield a general perspective for understanding multiple trade-offs including group fairness incompatibilities. It also suggests an alternate post-processing method for designing fair classifiers. On synthetic and real datasets, we demonstrate the use cases of our diagnostic, particularly on understanding the trade-off landscape between accuracy and fairness.
Universal and taxon-specific trends in protein sequences as a function of age.

Extant protein-coding sequences span a huge range of ages, from those that emerged only recently, to those present in the last universal common ancestor. Because evolution has had less time to act on young sequences, there might be 'phylostratigraphy' trends in any properties that evolve slowly with age. A long-term reduction in hydrophobicity and hydrophobic clustering was found in previous, taxonomically restricted studies. Here we perform integrated phylostratigraphy across 435 fully sequenced species, using sensitive HMM methods to detect protein domain homology. We find that the reduction in hydrophobic clustering is universal across lineages. However, only young animal domains have a tendency to have higher structural disorder. Among ancient domains, trends in amino acid composition reflect the order of recruitment into the genetic code, suggesting that the composition of the contemporary descendants of ancient sequences reflects amino acid availability during the earliest stages of life, when these sequences first emerged.
Semiorthogonal decompositions of equivariant derived categories of invariant divisors

Given a smooth variety $X$ with an action of a finite group $G$, and a semiorthogonal decomposition of the derived category, $\mathcal{D}([X/G])$, of $G$-equivariant coherent sheaves on $X$ into subcategories equivalent to derived categories of smooth varieties, we construct a similar semiorthogonal decomposition for a smooth $G$-invariant divisor in $X$ (under certain technical assumptions). Combining this procedure with the semiorthogonal decompositions constructed in [PV15], we construct semiorthogonal decompositions of some equivariant derived categories of smooth projective varieties.
Wall-Modeled Large-Eddy Simulation of Turbulent Boundary Layers with Mean-Flow Three-Dimensionality

We examine the performance of wall-modeled large-eddy simulation (WMLES) to predict turbulent boundary layers (TBLs) with mean-flow three-dimensionality. The analysis is performed for an ordinary-d...
Combinatorial approach to spreading processes on networks

Stochastic spreading models defined on complex network topologies are used to mimic the diffusion of diseases, information, and opinions in real-world systems. Existing theoretical approaches to the characterization of the models in terms of microscopic configurations rely on some approximation of independence among dynamical variables, thus introducing a systematic bias in the prediction of the ground-truth dynamics. Here, we develop a combinatorial framework based on the approximation that spreading may occur only along the shortest paths connecting pairs of nodes. The approximation overestimates dynamical correlations among node states and leads to biased predictions. Systematic bias is, however, pointing in the opposite direction of existing approximations. We show that the combination of the two biased approaches generates predictions of the ground-truth dynamics that are more accurate than the ones given by the two approximations if used in isolation. We further take advantage of the combinatorial approximation to characterize theoretical properties of some inference problems, and show that the reconstruction of microscopic configurations is very sensitive to both the place where and the time when partial knowledge of the system is acquired.
Score-informed Networks for Music Performance Assessment

The assessment of music performances in most cases takes into account the underlying musical score being performed. While there have been several automatic approaches for objective music performance assessment (MPA) based on extracted features from both the performance audio and the score, deep neural network-based methods incorporating score information into MPA models have not yet been investigated. In this paper, we introduce three different models capable of score-informed performance assessment. These are (i) a convolutional neural network that utilizes a simple time-series input comprising of aligned pitch contours and score, (ii) a joint embedding model which learns a joint latent space for pitch contours and scores, and (iii) a distance matrix-based convolutional neural network which utilizes patterns in the distance matrix between pitch contours and musical score to predict assessment ratings. Our results provide insights into the suitability of different architectures and input representations and demonstrate the benefits of score-informed models as compared to score-independent models.
Analysts’ treatment of nonrecurring items in street earnings ☆

Abstract Given the recent controversy over deviations of street earnings from GAAP earnings, we show that the nonrecurring items that analysts include in street earnings are more persistent and have higher valuation multiples than those items they exclude from street earnings. In addition, we find no evidence that the pricing differential between the included and excluded items leads to future abnormal returns. If, as analysts claim, the primary use of street earnings is to value a stock, then our results suggest that analysts do have expertise in processing earnings information and that certain items appear justifiably excluded.
The Impact of Legalized Abortion on Crime

We offer evidence that legalized abortion has contributed significantly to recent crime reductions. Crime began to fall roughly eighteen years after abortion legalization. The five states that allowed abortion in 1970 experienced declines earlier than the rest of the nation, which legalized in 1973 with Roe v. Wade. States with high abortion rates in the 1970s and 1980s experienced greater crime reductions in the 1990s. In high abortion states, only arrests of those born after abortion legalization fall relative to low abortion states. Legalized abortion appears to account for as much as 50 percent of the recent drop in crime.
Scenarios and the growth of knowledge: Notes on the epistemic element in scenario building

Abstract Scenarios raise a very remarkable challenge. They are a special category of thought experiments and as such they deal with the domain of the “possible” and “probable”, i.e. with the world of speculation. Nevertheless they are of a crucial practical importance for public policy, management and strategic thinking in general: any premeditated significant action has to be preceded by such a thought experiment that anticipates the possibility of its outcomes and its implications. The question is then, how could speculation have such a crucial epistemic role? What kind of knowledge, if any, do scenarios produce? What is the epistemic role of scenarios? The objective of this article is to discuss the controversial but crucial issue of the epistemic functions of scenarios and to outline several possible approaches to it. The article explores the relevance in this respect of the research that has been already done on thought experiments, de-biasing, deductive arguments and uncertainty—and complexity—coping cognitive devices while indicating the potential contribution of that literature to the further development of the scenario building practice and of the futures methodology.
Urban Growth in the 1990s: Is City Living Back?

The 1990s were an unusually good decade for the largest American cities and, in particular, for the cities of the Midwest. However, fundamentally urban growth in the 1990s looked extremely similar to urban growth during prior post–war decades. The growth of cities was determined by three main trends: (1) cities with strong human capital bases grew faster than cities without skills, (2) people moved to warmer, drier places, and (3) cities built around the automobile replaced cities that rely on public transportation. Although the negative impact of population density diminished slightly in the 1990s, there is no real evidence for a return to large, dense cities.
MODELING AND FORECASTING REALIZED VOLATILITY

This paper provides a general framework for integration of high-frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting financial asset return volatilities, correlations, and distributions rely on restrictive and complicated parametric multivariate ARCH or stochastic volatility models, which often perform poorly at intraday frequencies. Use of realized volatility constructed from high-frequency intraday returns, in contrast, permits the use of traditional time series procedures for modeling and forecasting. Building on the theory of continuous-time arbitrage-free price processes and the theory of quadratic variation, we formally develop the links between the conditional covariance matrix and the concept of realized volatility. Next, using continuously recorded observations for the Deutschemark / Dollar and Yen / Dollar spot exchange rates covering more than a decade, we find that forecasts from a simple long-memory Gaussian vector autoregression for the logarithmic daily realized volatilities perform admirably compared to popular daily ARCH and related models. Moreover, the vector autoregressive volatility forecast, coupled with a parametric lognormal-normal mixture distribution implied by the theoretically and empirically grounded assumption of normally distributed standardized returns, gives rise to well-calibrated density forecasts of future returns, and correspondingly accurate quantile estimates. Our results hold promise for practical modeling and forecasting of the large covariance matrices relevant in asset pricing, asset allocation and financial risk management applications.
The Invisibility Factor: The Limits of Public Choice Theory and Public Institutions

This Article's thesis is that because public choice theory underestimates the ability of the majority to influence the political process, it is of limited use as a predictive tool. More specifically, this Article suggests that in certain circumstances, public choice theory incorrectly predicts whether a special interest group can successfully pass its legislation. This Article examines this thesis in the context of state education funding reform and hows that public choice theory would have incorrectly predicted some recent legislative responses in that area.
The Consequences of Collective Action: An Incomplete-Contracts Approach

Public policy may be determined as much by what cannot be agreed to by politicians and organized interests as by what can. Focusing on the inability of organized groups to credibly promise that their members will fully report revenues to tax authorities, I develop an incomplete-contracts lobbying model that shows that the provision of collective goods may be influenced by the anticipated tax compliance of economic sectors as well as by the organization of interests. Data from a survey of firms in Eastern Europe and the former Soviet Union are broadly supportive of the theory: the ability of firms to hide revenues from tax authorities rivals conventional collective-action variables in explaining variation in collective-goods provision, but only in that part of the postcommunist world where differences in revenue hiding across sectors are especially large.
INTELLECTUAL PROPERTY RIGHTS AND DISPUTE SETTLEMENT IN THE WORLD TRADE ORGANIZATION

With the advent of the TRIPS Agreement, international disputes about governmental regulation of intellectual property rights (IPRs) are now subject to adjudication within the WTO dispute resolution mechanism. The standard model used by economists to explain dispute settlement procedures is misleading, for the process is not about preventing countries from exercising market power. Rather, the system is designed to resolve political market failures arising within countries that would be harmful to market access for foreign firms. These issues arise particularly in the context of IPRs, which may be used as cross-market bargaining chips. This possibility is illustrated by the petition of Ecuador to suspend concessions in this area for European firms in the context of the EU – Banana case. The scope of such an approach remains unclear and there are many fundamental questions deserving close analysis. In this paper I make several basic points relating to the economics of IPRs and the World Trade Organization’s (WTO) dispute settlement process. 1 These comments underscore the fact that the injection of IPRs into the global trading system raises a new dimension for settling disputes.
The impact of rights plans on proxy contests: Reevaluating Moran v. Household International

American corporate management has sought to insulate itself from dissident shareholders' voting power by enacing "Rights Plans." Rights Plans reduce a dissident shareholder's chances of winning a proxy contest by restricting the number of shares that a dissident group can own. Most Rights Plans severely penalize a dissident shareholder that owns more that a limited amount, or trigger level, of 15% to 20% of the corporation's voting common stock. Rights Plans can stop dissident from forming coalitions with other shareholders if collectively they would own a greater precentage of voting stock than this trigger level. We conclude that in the absence of Rights Plans, dissidents could have acquired larger blocks of stock (or formed stronger coaliitions), whichin turn would have led to a higher proportion of dissident victories.
Can Direct Democracy Be Made Deliberative

Every election cycle a great number of citizens take to the polls to vote on public policy matters directly. Direct democracy has problems. And an account of deliberative democracy  far from being a source to critique direct democracy  might provide a solution. I have three goals in this short Essay. First, I hope to identify some problems with the mechanisms of direct democracy that most states and many cities throughout the country employ: the initiative and the referendum. Next, I will offer a potential solution to these institutional problems using aspects of the theory of deliberative democracy, a theory often marshaled to undermine direct democracy. Finally, I will spell out why this design project should be of especial interest to lawyers.
Does the GMAT Matter for Executive MBA Students? Some Empirical Evidence

I examine the relation of several factors, including the GMAT score, undergraduate background, and work experience to academic success in an executive MBA program. The GMAT score was found to have ...
Information, Incentive Alignment, and Company Loan Financing of Insider Trades

Insider acquisitions of shares are supposed to align the interests of managers and shareholders. Thus, they are typically viewed as positive signals. However, if the transactions do not put insiders' wealth at risk, perhaps this conclusion is a bit premature. We focus on loan financing of insider share acquisitions to test this idea. Our results indicate that loan financed insider purchases and option exercises earn smaller profits than non loan-financed counterparts. Our results also suggest that loan-financed insider purchases are an additional method to move an executive quickly to a target level of incentives. Based on these results, we conclude that (a) not all insider trades are alike, (b) insiders recognize when they are “playing with other people’s money,” and (c) loan-financed purchases play an important role in incentive alignment.
Technology trap and poverty trap in Sub-Saharan Africa

Since the industrial revolution, advances in science and technology have continuously accounted for most of the growth and wealth accumulation in leading industrialized economies. In recent years, the contribution of technological progress to growth and welfare improvement has increased even further, especially with the globalization process which has been characterized by exponential growth in exports of manufactured goods. This paper establishes the existence of a technology trap in Sub-Saharan Africa. It shows that the widening income and welfare gap between Sub-Saharan Africa and the rest of world is largely accounted for by the technology trap responsible for the poverty trap. This result is supported by empirical evidence which suggests that if countries in Sub-Saharan Africa were using the same level of technology enjoyed by industrialized countries income levels in Sub-Saharan Africa would be significantly higher. The result is robust, even after controlling for institutional, macroeconomic instability and volatility factors. Consistent with standard one-sector neoclassical growth models, this suggests that uniform convergence to a worldwide technology frontier may lead to income convergence in the spherical space. Overcoming the technology trap in Sub-Saharan Africa may therefore be essential to achieving the Millennium Development Goals and evolving toward global convergence in the process of economic development.
Liability for Direct Advertising of Drugs to Consumers: An Idea Whose Time Has Not Come

It’s a puzzlement: If anyone had taken a poll of product liability cognoscenti a decade ago as to whether the learned intermediary rule would survive in the face of the onslaught of massive advertising of drugs in the media, the overwhelming majority would have answered in the negative. The well entrenched doctrine requires that a pharmaceutical manufacturer provide warnings of risks attendant to ingesting a prescription drug to the physician only and not to the patient. The principal rationale for the learned intermediary rule is that information concerning risks should be delivered to the physician who is tutored in the science of understanding risk and evaluating risk contextually. The physician is then charged with the responsibility of picking and choosing among the multitude of risks posed by a drug and then deciding how the risk information is to be communicated to the patient. The basis for the rule is seriously undercut when drugs such as Lipitor, Rogaine, Viagra, and Celebrex are huckstered to the public as if they were M&M candies. If one advertises directly to patients seeking to entice them to urge their physicians to prescribe a drug then one should have a concomitant duty to directly warn the patient of risks associated
Updating the poverty estimates in Serbia in the absence of micro data : a microsimulation approach

The continued poverty impact of the financial crisis in Serbia is difficult to establish beyond 2010 because of the lack of survey data. This paper tackles this difficulty. It uses a micro-simulation approach that accounts for a key pathway of the financial crisis in Serbia, the labor market. The results suggest a further increase in poverty in 2011 on account of a continued deterioration of the labor market indicators and despite a recovering gross domestic product. In order to evaluate the forecast, the model is applied to generate forecasts for previous years (2009 and 2010), which are compared with realized poverty estimates. The micro-simulation model performs well in predicting poverty dynamics during 2009-10 and less so during 2008-09. The accuracy of the predictions improves when the response of the social protection system is accounted for.
Work and Play: International Evidence of Gender Equality in Employment and Sports

This article demonstrates a link between an economic and social feature of countries, the relative labor force participation rate of women, and a high-profile characteristic, the performance of women in international sports competitions. The relative labor force participation rate of women was a significant determinant of the number and type of medals won by a country’s women in the 2000 Sydney Summer Olympics as well as the likelihood of qualifying for the 1999 Women’s Soccer World Cup and performance in that competition. Thus, societies in which women have greater economic opportunities are ones that enable athletically talented women to reach their full potential.
Presidential Legitimacy through the Anti-Discrimination Lens

The Obama Administration’s deferred action programs granting temporary relief from deportation to undocumented immigrants have focused attention to questions regarding the legitimacy of presidential lawmaking. Immigration, though, is not the only context in which the President has exercised policymaking authority. This essay examines parallel instances of executive lawmaking in the anti-discrimination area. Presidential policies relating to workplace discrimination, environmental justice, and affirmative action share some of the key features troubling critics of deferred action yet have been spared from serious constitutional challenge. These examples underscore the unique challenges to assessing the validity of actions targeting traditionally disenfranchised groups – be they noncitizens, racial or ethnic minorities, or members of the lesbian, gay, bisexual, and transgender (LGBT) communities, for example. Just as prior generations grappled with the unique legitimacy concerns raised by judicial interventions to protect these interests, the current era of presidential lawmaking suggests the need for a distinct theory of legitimacy when the President acts to protect vulnerable populations.
The landscape of Japanese tobacco policy: law, smoking and social change

Japanese landscape painters use three perspectives-hei-en evokes the feeling of standing on the top of a mountain and gazing at other peaks; shin-en emphasizes the side of a scene that is hidden from view; and ko-en refers to the view from a valley up toward the heights. With these three points-of-view, painters working in the sansui (literally, hills and water) tradition are able to portray Japan's rich physical environment. The same perspectives help shed light on the current landscape of tobacco policy and smoking in Japan. Each of this paper's sections is based on one of the sansui approaches. First, observing other mountains from the top of one, the hei-en perspective, suggests the importance of understanding Japanese tobacco policy in its historical and comparative contexts. It illustrates Japan's long history of tobacco cultivation and regulation, as well as continuities in the regime of tobacco control. Taken together, hei-en's historical and comparative aspects emphasize the similarity of Japanese legal, political, and social practices with those of other nations. The shin-en perspective on that part of the mountain hidden from view illuminates the political economy of tobacco in Japan. Like the roots and branches that keep a hill from eroding, tobacco farmers, government bureaucrats, politicians, and big business constitute the not easily visible, interconnected elements of tobacco's political economy. More specifically, the key institutions include the Ministry of Finance (MoF), the majority owner of Japan Tobacco Inc. (JT); the Liberal Democratic Party (LDP), which dominates domestic politics; the tobacco grower's union; and tobacco retailers. Unified, they con-
Redefining the Rights of Undocumented Workers

Should a nation extend legal rights to those who enter the country illegally? The Supreme Court recently addressed this question when it held that unauthorized immigrants who are fired illegally for unionizing cannot recover monetary remedies. This has led to a significant decline in employment protections for unauthorized immigrants beyond the unionized sector. For example, some courts now question whether unauthorized immigrants can receive full remedies for sexual harassment, workplace discrimination, or onthe-job injuries. Scholars have criticized these losses but have yet to formulate a coherent framework for evaluating the employment rights of unauthorized immigrants. This article does so by distilling and applying several core principles at issue when employment laws conflict with immigration laws. I begin by explaining how the text and purpose of selected immigration and employment statutes show that Congress never intended to restrict unauthorized immigrants’ employment rights. Remedial restrictions not only harm the workplace protections at issue, they fail to discourage illegal immigration. Thus, neither legislative intent nor national immigration goals justify limiting the workplace remedies available to unauthorized immigrants. Although the future rights of unauthorized workers will turn partly on the issues of statutory purpose and immigration policy discussed in the early sections of the article, equally important are the consequences of diminished rights. Accordingly, the article concludes by explaining why restricting workplace protections based on status harms citizens as well as immigrants. Cunningham-Parmeter contends that employment protections are “rights of partial inclusion” that reflect a distinctive sphere the workplace where unauthorized immigrants should be placed on par with citizens in pursuing collective interests. In contrast to arguments that favor limiting resources to lawful residents, partial inclusion explains how employment protections can effectively preserve national identity while simultaneously enhancing unauthorized immigrants’ incentives for social investment. In doing so, partial inclusion furthers the community’s selfdefinition, while providing unauthorized immigrants with a sense of belonging in a world increasingly focused on their exclusion.
Understanding the alliance data

A considerable body of research utilizes large alliance databases (e.g., SDC, MERIT-CATI, CORE, RECAP, and BIOSCAN) to study interorganizational relationships. Understanding the strengths and limitations of these databases is crucial for informing database selection and research design. In this study I conduct an analysis of five prominent alliance databases. Focusing on technology alliances (those formed for the purposes of joint research or cross-technology transfer), I examine the databases' consistency of coverage and completeness, and assess whether different databases yield the same patterns in sectoral composition, temporal trends, and geographic patterns in alliance activity. I also replicate three previously published alliance studies to assess the impact of data limitations on research outcomes. The results suggest that the databases only report a fraction of formally announced alliances, which could have detrimental consequences for some types of research. However, the databases exhibit strong symmetries in patterns of sectoral composition, alliance activity over time, and geographic participation. Furthermore, the replications of previous studies yielded results that were highly similar to those obtained in the original studies. This study thus provides some reassurance that even though the databases only capture a sample of alliance activity, they may yield reliable results for many—if not all—research purposes. This information should help researchers make better-informed decisions about their choice of database and research design. Copyright © 2008 John Wiley & Sons, Ltd.
Toward Evidence-Based Evidence: Supporting Forensic Knowledge Claims in the Post-Daubert Era

This paper reconceptualizes the Daubert admissibility regime using the "evidence-based" metaphor. Although contemporary society is pervaded by calls for such things as medicine, policy, corrections, and crime prevention to be "evidence-based" and evidence is firmly associated with law, there has been little application of this notion in law and little recognition of the homology between evidence-based medicine and the Daubert inquiry. The paper argues that the Daubert inquiry may be conceived as a demand for "evidence about evidence," or "evidence-based evidence." It then uses the recent controversy over the admissibility of latent print (fingerprint) evidence to illustrate this notion. It shows that proponents of latent print evidence have had difficulty producing evidence about the reliability (or accuracy) of latent print evidence. Instead, trial courts have tended to find latent print admissible based on evidence that does not pertain directly to the accuracy of latent print evidence. Therefore, latent print evidence, as yet, is not "evidence-based evidence." Finally, the paper suggests that this state of affairs may explain the exclusion of latent print evidence in one recent case.
The Economic Winners and Losers of Legalized Gambling

This paper reviews the government role in the legalized gambling sector and addresses some of the major issues relevant to any normative analysis of what the government role should be. In particular, the paper reviews evidence identifying the economic "winners" and "losers" associated with the three largest sectors of the industry: commercial casinos, state lotteries, and Native American casinos. The paper also includes a discussion of the grow- ing Internet gambling industry. In addition to reviewing existing literature and evidence, the paper raises relevant questions and policy issues that have not yet been adequately addressed in the economics literature.
Dynamics, cycles, and sunspot equilibria in ‘genuinely dynamic, fundamentally disaggregative’ models of money

Abstract This paper pursues a line of Cass and Shell, who advocate monetary models that are “genuinely dynamic and fundamentally disaggregative” and incorporate “diversity among households and variety among commodities”. Recent search-theoretic models fit this description. We show that, like overlapping generations models, search models generate interesting dynamic equilibria, including cycles, chaos, and sunspot equilibria. This helps us understand how alternative models are related, and lends support to the notion that endogenous dynamics and uncertainty matter, perhaps especially in monetary economies. We also suggest such equilibria in search models may be more empirically relevant than in some other models.
Expert Prevalence, Persuasion and Price: What Trial Participants Really Think About Experts

The importance of expert witnesses to modern litigation is clear, but the lack of reliable data about experts and their effectiveness in court is remarkable. Several studies have touched on the issue in recent decades, but the most comprehensive research in the area is based upon survey responses collected in 1988 and 1991. To fill the gap, this study offers a two-step analysis of experts in actual civil jury trials. First, judicial records of trials revealed both the percentage of cases with experts and the number of experts per case. Second, surveys of the trial participants – judges, attorneys, experts and jurors – revealed factors that make an expert persuasive as well as some surprise responses debunking conventional wisdom surrounding experts. By empirically measuring the role of experts in actual litigation, we can establish what makes them effective, when different litigants disagree about experts and why, and how the handling of experts has changed over time.
Refugee Roulette in an Administrative Law Context: The Deja vu of Decisional Disparities in Agency Adjudication

In Refugee Roulette: Disparities in Asylum Adjudication (the Asylum Study), Professors Ramji-Nogales, Schoenholtz, and Schrag provide a comprehensive analysis of new data to document decisional disparities that undermine the fairness of asylum adjudication. The Asylum Study is an empirical project of remarkable scope. It examines patterns of asylum decisions at four different adjudication levels: at the asylum office interview, in immigration court, on administrative appeal to the Board of Immigration Appeals (BIA), and on petition for review to the federal courts of appeals. At each level, the Asylum Study generates empirical findings to support what we knew mostly by anecdote that there are eye-popping disparities in the grant
Productivity growth and welfare in a model of allocative inefficiency

We develop a model of learning-by-doing in human capital formation in the presence of allocative inefficiencies. The inefficiencies are a result of lobbying by firms to establish, or prevent, barriers to the perfectly competitive allocation of factors of production (labor). It is shown that lobbying may lead to a static welfare loss depending upon the elasticity of substitution between goods, and the relative lobbying power of firms. Further, productivity growth, via learning by doing, changes the relative lobbying power over time. This may magnify or diminish the static welfare loss in the long-run depending on the level of initial misallocation. Therefore, differences in initial lobbying power and rate of productivity growth between sectors determine the long-run effects of lobbying.
Fiscal Stress and the Allocation of Expenditure Responsibilities between State and Local Governments: An Exploratory Study:

fects the allocation of expenditure responsi bilities between state and local governments. Fiscal condition refers to "the capacity of governments to meet financial and service level obligations" (Hendrick et al. 2006, 1). A decline in such capacity equates to fiscal stress. Studies that have looked at the fiscal relationship between state and local govern ments often focus on how fiscal institutions such as tax and expenditure limits (TELs) have changed the structure and size of the state-local sector (see, for instance, Mullins and Joyce 1996). A few studies have provided a descriptive account of how recent state fis cal stress has affected the fiscal relationship between states and their local governments. A single case study by Conant (2003) found that fiscal stress led to a reduction in state aid to local governments. Kalambokidis and Reschovsky (2005) observed that budget shortfalls from 2001 to 2004 forced states
Climate Change and the Clean Air Act

In 2003, the Environmental Protection Agency formally refused to regulate greenhouse gas emissions from automobiles, explaining that it had no authority under the Clean Air Act to undertake such regulation and that it would, in any event, decline to exercise such authority for various policy reasons. In Massachusetts v. EPA, the Supreme Court rejected EPA's decision on both counts. The Court held that the Clean Air Act gives the Environmental Protection Agency the authority to regulate greenhouse gases and it narrowly circumscribed the circumstances under which the agency could refuse to decide whether greenhouse gases may endanger public health or welfare. This Article, written before the Supreme Court's decision was announced and based on the author's briefs for petitioners in the case, examines in detail the reasons why EPA's views on statutory authority and discretion were incorrect.
Vertical Integration and Exclusivity in Platform and Two-Sided Markets

This paper develops techniques to analyze the adoption decisions of both consumers and flrms for competing platform intermediaries in two-sided markets, and applies the methodology to empirically measure the impact of vertical integration and exclusive contracting in the sixth-generation of the U.S. videogame industry (2000-2005). I flrst introduce a framework to structurally estimate consumer demand in these types of hardware-software markets which (i) simultaneously analyzes both hardware and software adoption decisions; (ii) accounts for dynamic issues including the selection of heterogenous consumers across platforms, durability of goods, and agents’ timing of purchases; and (iii) explicitly provides the marginal contribution of an individual software title to each platform’s installed base of users. Demand results show the gains obtained by a platform provider from exclusive access to certain software titles can be large, and failure to account for dynamics, consumer heterogeneity, and multiple hardware purchases signiflcantly biases estimates. I next specify dynamic network formation game to model the adoption decision of hardware platforms by software providers. Counterfactual experiments indicate that vertical integration and exclusivity beneflted the smaller entrant platforms and not the dominant incumbent, which stands contrary to the interpretation of exclusivity as primarily a means of foreclosure and entry deterrence.
Corporate diversification and firm value during economic downturns

Abstract This paper examines the effect of corporate diversification on firm value during periods of economic downturns. Analysis of diversified firms’ valuation during recessionary periods reveals a significant increase in relative value of diversified firms. The observed improvement in the relative valuation is only a temporary phenomenon, which disappears in the four quarters following the trough of the recession. We do not find support to the hypothesis that the improvement in relative valuation of diversified firms during economic downturns is attributed to the ability of diversified firms to utilize broader external capital markets. We demonstrate that the improvement in relative valuation is largely driven by diversified firms that are financially constrained, and, therefore, attribute the observed improvement to more efficient internal capital allocation during recessions.
Empathy and Article III: Judge Weinstein, Cases and Controversies

The question of whether judges ought to be empathetic has been hotly debated in recent years. This volume celebrating the life and achievements of Judge Jack Weinstein presents an ideal opportunity to productively focus and narrow the empathy debate. Problematically, this debate generally treats judging as a monolithic concept. To debate whether empathy is a desirable attribute of judges as a general matter is to overlook important distinctions between trial, appellate, and Supreme Court jurists, and between federal and state courts. Using Judge Weinstein’s approach to judging as a touchstone, I explore the role of empathy for Article III judges, and for federal district court judges in particular.
Savings selectivity bias, subjective expectations and stock market participation

Studies of household stock market participation report low participation rates. The explanations cited are that the fixed costs associated with participation and high risk aversion discourage households from buying stocks. However, the low participation rate findings are unchallenged. We argue that because prior studies fail to recognize that not all households save, there exists a selection bias when estimating the household participation rate. After correcting for this selection bias, as well as accounting for the influence of subjective expectations on market participation, we show that the unconditional probability of participating in the stock market would increase twofold.