When Tuna Still Isn’t Always Tuna: Federal Food Safety Regulatory Regime Continues to Inadequately Address Seafood Fraud

In 2012 alone, Americans consumed approximately 4.5 billion pounds of seafood, over 90% of which was imported. Simply put, Americans eat a lot of seafood, with upwards of 500 different species available to satiate the demand. Consequently, imported and domestic seafood in the United States is a thriving 80.2 billion dollar market, with certain highly desired species of fish fetching steep prices. One fundamental assumption of the consumer-driven market is that the label on the seafood correctly identifies the species of seafood, thereby, among other things, justifying the market price. It is increasingly clear, however, that this assumption is often not the case for seafood: many consumers are awakening to the upsetting and dangerous reality that the premium-priced, ecologically-certified, wild Atlantic salmon they ordered at the restaurant or picked up at the grocer is perhaps the much less-expensive and arguably unsustainable farm-raised salmon; or that their sashimi ahi tuna, prized for its delicate flavor and light flesh, is potentially the snake mackerel, a species of fish whose oils are known to cause severe gastrointestinal problems. The dilemma consumers face is seafood fraud: the substitution, misrepresentation, or mislabeling of a species of seafood that has become progressively prevalent with the increase of globalized trade, consumer demand for seafood, increased consumer demand for sustainably-sourced seafood, and the availability of reliable and inexpensive DNA technology that can test the flesh of the food item to determine its species and origin. Whether seafood fraud is intentional or unintentional, it is an economic, environmental, and food safety harm. Particularly because of the severity of the threat to food safety, this comment examines the adequacy of the existing federal regulatory regime addressing seafood fraud, specifically focusing on potential impacts of the Food Safety and Modernization Act (FSMA) on seafood fraud. Part I of this comment explores what exactly seafood fraud is and the negative impacts this has on the economy, the environment, and human health. Part II lays out the different federal agencies responsible for regulating seafood fraud and briefly analyzes the agencies’ attempts to address the problem. Part III summarizes the origin and scope of FSMA and highlights potential new powers and opportunities it gives the Food and Drug Administration (FDA) for addressing seafood fraud. Finally, part IV concludes that even with FSMA, there remain significant problems with the current food safety regime that inhibit real action on addressing seafood fraud on the federal level and discusses other potential alternative approaches, including Senator (then Representative) Ed Markey’s recently re-introduced Safety And Fraud Enforcement for Seafood Act (SAFE Seafood Act)

Examining the potential of Conditional Cash Transfer for stemming Cape Flats Gang violence: A Directional Policy research project

Many low and middle-income countries have either implemented or considered conditional or unconditional cash transfers to poor households as a means of alleviating poverty. Evidence from pilot schemes in many developed and developing economies, including those in Africa, suggests that cash transfers do not only alleviate poverty; they also promote social cohesion and reduce the propensity for violent responses. For example, studies have shown a direct impact of cash transfers on Intimate Partner Violence (IPV). In some studies, the rate of IPV (including emotional violence) was significantly reduced when one of the partners was a beneficiary of cash transfer. However, there are limited studies on the potential of Conditional Cash Transfers (CCTs) for stemming gang violence. Our study contributes to filling this gap. We examine here the possibilities of conditional cash transfers for stemming intractable gang-related violence in the Cape Flats

The Problem of Wage Theft

Wage theft inflicts serious harm on America\u27s working poor but has received little attention from policymakers seeking to address income inequality in the United States. This Article provides a comprehensive analysis of the causes of the wage theft crisis and the failure of the current enforcement regime to address it. It argues that existing policy reforms will fail, because they misunderstand the nature of the crisis and the incentives that employers face when deciding to steal workers\u27 wages. It then proposes series of reforms that could work, while arguing that changing the economic calculus alone will be unlikely to solve the problem if social norms remain unchanged

Concentrated Enforcement

When enforcement resources are limited, how should the scarce enforcement resources be allocated to increase compliance with the law? The answer to this question can determine to what extent the law on the books translates to the law in practice. A dominant school of thought in the tax literature suggests that they should be allocated based on a worst-first method, whereby the individuals likely to be most noncompliant are targeted. However, while worst-first methods can encourage all individuals to increase compliance so as not to be deemed the worst, they can also provide cover to engage in noncompliance that is perceived moderate for the relevant population. This dynamic can become most problematic in highly noncompliant populations. In such populations, existing, high levels of noncompliance, and underlying, structural causes of the high noncompliance can serve as coordinating mechanisms, providing mutual assurance of low compliance. Moreover, worst-first theories do not provide a comprehensive explanation for the group and project-based enforcement practices that are found in a number of actual enforcement settings. In response to these deficits, this Article draws on work from across different disciplines to develop a new theory for the allocation of scarce tax enforcement resources. This Article suggests that, under certain conditions, deterrence can be enhanced by allocating scarce enforcement resources among a low-compliance population of taxpayers through a process called concentrated enforcement. After setting forth the theoretical case for concentrated enforcement, this Article examines how it might apply in the cash business tax sector, a highly noncompliant sector that presents particular challenges for worst-first methods. This Article concludes that concentrated enforcement may increase compliance, meriting its application and empirical evaluation

Concentrated Enforcement

When enforcement resources are limited, how should the scarce enforcement resources be allocated to increase compliance with the law? The answer to this question can determine to what extent the law on the books translates to the law in practice. A dominant school of thought in the tax literature suggests that they should be allocated based on a “worst-first” method, whereby the individuals likely to be most noncompliant are targeted. However, while “worst-first” methods can encourage all individuals to increase compliance so as not to be deemed the “worst,” they can also provide cover to engage in noncompliance that is perceived moderate for the relevant population. This dynamic can become most problematic in highly noncompliant populations. In such populations, existing, high levels of noncompliance, and underlying, structural causes of the high noncompliance can serve as coordinating mechanisms, providing mutual assurance of low compliance. Moreover, “worst-first” theories do not provide a comprehensive explanation for the group and project-based enforcement practices that are found in a number of actual enforcement settings. In response to these deficits, this Article draws on work from across different disciplines to develop a new theory for the allocation of scarce tax enforcement resources. This Article suggests that, under certain conditions, deterrence can be enhanced by allocating scarce enforcement resources among a low-compliance population of taxpayers through a process called concentrated enforcement. After setting forth the theoretical case for concentrated enforcement, this Article examines how it might apply in the cash business tax sector, a highly noncompliant sector that presents particular challenges for “worst-first” methods. This Article concludes that concentrated enforcement may increase compliance, meriting its application and empirical evaluation

Development of a Social Engineering eXposure Index (SEXI) using Open-Source Personal Information

Millions of people willingly expose their lives via Internet technologies every day, and even the very few ones who refrain from the use of the Internet find themselves exposed through data breaches. Billions of private information records are exposed through the Internet. Marketers gather personal preferences to influence shopping behavior. Providers gather personal information to deliver enhanced services, and underground hacker networks contain repositories of immense data sets. Few users of Internet technologies have considered where their information is going or who has access to it. Even fewer are aware of how decisions made in their own lives expose significant pieces of information, which can be used by cyber hackers to harm the very organizations with whom they are affiliated. While this threat can affect any person holding any position at an organization, upper management poses a significantly higher risk due to their level of access to critical data and finances targeted by cybercrime. The goal of this research was to develop and validate a Social Engineering eXposure Index (SEXI)™ using Open-Source Personal Information (OSPI) to assist in identifying and classifying social engineering vulnerabilities. This study combined an expert panel using the Delphi method, developmental research, and quantitative data collection. The expert panel categorized and assessed information privacy components into three identifiability groups, subsequently used to develop an algorithm that formed the basis for a SEXI. Validation of the algorithm used open-source personal information found on the Internet for 50 executives of Fortune 500 organizations and 50 Hollywood celebrities. The exposure of each executive and persona was quantified and the collected data were evaluated, analyzed, and presented in an anonymous aggregated form. Phase 1 of this study developed and evaluated the SEXI benchmarking instrument via an expert panel using the Delphi expert methodology. During the first round, 3,531 data points were collected with 1,530 having to do with the demographics, qualifications, experience, and working environments of the panel members as well as 2,001 attributing levels of exposure to personal information. The second Delphi round presented the panel members with the feedback of the first-round tasking them with categorizing personal information, resulting in 1,816 data points. Phase 2 of this study used the composition, weights, and categories of personal information from Phase 1 in the development of a preliminary SEXI benchmarking instrument comprised of 105 personal information items. Simulated data was used to validate the instrument prior to the data collection. Before initiating Phase 3, the preliminary SEXI benchmarking instrument was fully tested to verify the accuracy of recorded data. Phase 3 began with discovering, evaluating, and validating repositories of publicly available data sources of personal information. Approximately two dozen sources were used to collect 11,800 data points with the SEXI benchmarking index. Upon completion of Phase 3, data analysis of the Fortune 500 executives and Hollywood personas used to validate the SEXI benchmarking index. Data analysis was conducted in Phase 3 by one-way Analysis of Variance (ANOVA). The results of the ANOVA data analysis from Phase 3 revealed that age, gender, marital status, and military/police experience were not significant in showing SEXI differences. Additionally, income, estimated worth, industry, organization position, philanthropic contributions are significant, showing differences in SEXI. The most significant differences in SEXI in this research study were found with writers and chief information officers. A t-test was performed to compare the Fortune 500 executives and the Hollywood personas. The results of the t-test data analysis showed a significant difference between the two groups in that Hollywood Personas had a higher SEXI than the Fortune 500 Executives suggesting increased exposure due to OSPI. The results of this research study established, categorized, and validated a quantifiable measurement of personal information. Moreover, the results of this research study validated that the SEXI benchmarking index could be used to assess an individual’s exposure to social engineering due to publicly available personal information. As organizations and public figures rely on Internet technologies understanding the level of personal information exposure is critical is protecting against social engineering attacks. Furthermore, assessing personal information exposure could provide an organization insight into exposed personal information facilitating further mitigation of threats or potential social engineering attack vectors. Discussions and implications for future research are provided

Policy and Place: A Spatial Data Science Framework for Research and Decision-Making

abstract: A major challenge in health-related policy and program evaluation research is attributing underlying causal relationships where complicated processes may exist in natural or quasi-experimental settings. Spatial interaction and heterogeneity between units at individual or group levels can violate both components of the Stable-Unit-Treatment-Value-Assumption (SUTVA) that are core to the counterfactual framework, making treatment effects difficult to assess. New approaches are needed in health studies to develop spatially dynamic causal modeling methods to both derive insights from data that are sensitive to spatial differences and dependencies, and also be able to rely on a more robust, dynamic technical infrastructure needed for decision-making. To address this gap with a focus on causal applications theoretically, methodologically and technologically, I (1) develop a theoretical spatial framework (within single-level panel econometric methodology) that extends existing theories and methods of causal inference, which tend to ignore spatial dynamics; (2) demonstrate how this spatial framework can be applied in empirical research; and (3) implement a new spatial infrastructure framework that integrates and manages the required data for health systems evaluation. The new spatially explicit counterfactual framework considers how spatial effects impact treatment choice, treatment variation, and treatment effects. To illustrate this new methodological framework, I first replicate a classic quasi-experimental study that evaluates the effect of drinking age policy on mortality in the United States from 1970 to 1984, and further extend it with a spatial perspective. In another example, I evaluate food access dynamics in Chicago from 2007 to 2014 by implementing advanced spatial analytics that better account for the complex patterns of food access, and quasi-experimental research design to distill the impact of the Great Recession on the foodscape. Inference interpretation is sensitive to both research design framing and underlying processes that drive geographically distributed relationships. Finally, I advance a new Spatial Data Science Infrastructure to integrate and manage data in dynamic, open environments for public health systems research and decision- making. I demonstrate an infrastructure prototype in a final case study, developed in collaboration with health department officials and community organizations.Dissertation/ThesisDoctoral Dissertation Geography 201

State of Health Equity Movement, 2011 Update Part C: Compendium of Recommendations DRA Project Report No. 11-03

State of Health Equity Movement, 2011 Update Part C: Compendium of Recommendations DRA Project Report No. 11-0

Measurement of fisheries compliance outcomes : a preliminary national study : FRDC final report

This report presents the results of a project undertaken by a group of Australia and United States based fishery compliance experts to assess and compare methods for measuring fisheries compliance outcomes that can be used to assess and compare the effectiveness of fishery enforcement and compliance assistance activities. This eight month project was requested in 2013 by Australia’s National Fisheries Compliance Committee (NFCC) as a way to provide fisheries compliance groups with improved methods for measuring and tracking the effectiveness of their activities and for justifying and managing their budgets