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Item The Republic of Georgia: Public Opinion about NATO and the Implications for U.S. Foreign Policy(2016-02-02T21:47:03Z) Hanson, Zachary C.This paper explores how various socioeconomic measures affect Georgian residents' opinions on joining NATO. These measures include education level, knowledge of the English language, and job satisfaction. Through statistical analysis and the use of a comprehensive regional dataset, it is found that there is a statistically significant relationship between education level, knowledge of the English language, job satisfaction, and support for joining NATO. These findings have a high relevance to current U.S. foreign policy as the majority of U.S. led initiatives have been geared towards enhancing Western support in the Republic of Georgia through English language courses and cross-cultural democracy training.Item The Implications of Shortening Early Voting Periods: A Case Study from Mecklenburg County, North Carolina(2016-05-05T14:39:46Z) Weil, MatthewEarly voting is a widely available convenience voting option, yet research into exactly who casts a ballot early has produced mixed results. Researchers have simultaneously shown that early voters are wealthier and whiter than average, or older and more habitual voters, or more heavily minority than average. Most research has used self-reported survey data both for turnout and method of voting. The author utilizes state-compiled data from Mecklenburg County, North Carolina combining registered voters’ demographic and method of voting information for all elections over a ten-year time horizon. The results show that self-identified minority racial status is associated with between a 6.9 and 16.9 percentage point increase in the likelihood that a voter will choose to vote early over a non-minority voter during the last four federal elections beginning in 2008. These findings will inform ongoing litigation in North Carolina and across the country about the disparate impact of reductions in the availability of early voting as well as the need for election administrators to more efficiently deploy resources in preparation for early voting.Item Undocumented Migration Unveiled: The Driving Effect of Violence, Income, and Freedom on Migration from Latin America to the United States(2016-05-31T17:44:58Z) Croce, Joseph A.Existing research on the effect of violence on undocumented migration from Central and South America to the United States is limited and generally broad in its findings. To fill this gap, this paper theorizes that high violence rates are associated with increased undocumented migration from the region. Using multivariate regression models and country-year data, the results show that high violence, lower income levels, and less freedom within the origin countries are associated with increased migration, while political and economic conditions within the United States are not. In light of these findings, the paper offers policy considerations that can more effectively address the causes of undocumented migration from these countries, which are also applicable to address the recent influx of unaccompanied children since 2011.Item Determinants of Forced Migration: The Varying Effects of Violence and Economic Conditions on Syrian Refugee Flight(2016-12) Byrne, MaureenThe majority of existing research on the impact of civil war on forced migration flows uses observations at the annual-global level, limiting the applicability of results to explaining aggregate trends. This article studies refugee flows from Syria to Jordan from 2012-2015 at the weekly level to test how violence and economic conditions affect the fluctuation of migration processes. The results of regression analysis offer support for the argument that all violence does not affect migration decisions uniformly; rather some types of violence produce higher migration flows, while others, such as chemical warfare, render conditions too unsafe to flee. Furthermore, while economic conditions in the origin country affect migration flows, conditions in the destination country do not, suggesting that economic opportunities outside the country are less consequential as a determinant of forced migration during civil war. The research demonstrates the importance of using data at low levels of temporal aggregation to uncover causal mechanisms underlying refugee flight.Item Job Training Programs for Dislocated Workers: The Positive Effects of the Workforce Innovation and Opportunity Act(2016-12) Pedro, ChuckThere has been a substantial amount of research the past several decades measuring the effectiveness of federally subsidized Department of Labor (DOL) programs to assist the unemployed. However, there is little to no research yet evaluating the most recent renewal of programs as defined by the Workforce Innovation and Opportunity Act (WIOA) of 2014. This paper measures the WIOA’s effectiveness in helping dislocated workers who have obtained new skills, training, or education - a critically important opportunity for those who have experienced a job separation. The analysis uses probit to predict the probability of workers entering employment after training and propensity score matching on observational data to approximate an experimental setup. The matched data are then used in estimating the change in earnings conditional upon finishing training. The results are positive and statistically significant in support of the hypothesis that WIOA services help the unemployed to upgrade their skills and improve their prospects in the workforce.Item Determinants of Military Expenditure for Deterrence: Interaction with Nuclear Weapons, Democracies, and Alliances(2016-12) Kim, KennethDuring his campaign trail, the President-elect announced increasing military expenditure to enable deterrence to maintain the security of the United States. However, limited quantitative research exists to determine if military expenditures effectively support deterrence. Moreover, current research does not estimate if possession of nuclear weapons, a democratic form of government, and alliances contribute to prohibiting militarized conflicts through deterrence. This article examines the determinants of military expenditures and its effects on increased deterrence by analyzing ten countries engaged in deterrence. A regression of military expenditures as the dependent variable establishes a baseline to identify predicted values based on the theories of nuclear deterrence, democracy peace, and free riding of defense burden within alliances. The regression further explores interactions between possession of nuclear weapons and democracies, between democracies and alliances, and between possession of weapons and alliances. Limited results convey that deterrence can be increased with increased military expenditure but at a cost.Item Algorithmic Discrimination in the U.S. Justice System: A Quantitative Assessment of Racial and Gender Bias Encoded in the Data Analytics Model of the Correctional Offender Management Profiling for Alternative Sanctions (COMPAS)(2017-04) Li, YubinThe fourth-generation risk-need assessment instruments such as Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) have opened the opportunities for the use of big data analytics to assist judicial decision-making across the criminal justice system in U.S. While the COMPAS system becomes increasingly popular in supporting correctional professionals’ judgement on an offender’s risk of committing future crime, little research has been published to investigate the potential systematic bias encoded in the algorithms behind these assessment tools that could possibly work against certain ethnic or gender groups. This paper uses two-sample t-test and ordinary least-square regression model to demonstrate that COMPAS algorithms systemically generates a higher risk score for African-American and male offenders in terms of the risk of failure to appear, risk of recidivism, and risk of violence. Although race was explicitly excluded when the COMPAS algorithms were developed, the results showed that such an analytic model still systematically discriminates against African- American offenders. This paper introduced the importance of examining algorithmic fairness in big data analytic applications and offers the methodology as well as tools to investigate systematic bias encoded in machine leaning algorithms. Additionally, the implications of this paper also suggest that simply removing the protected variable in a big data algorithm could not be sufficient to eliminate the systematic bias that can still affect the protected groups, and that further research is needed for solutions to thoroughly address the algorithmic bias in big data analytics.Item Predictive Policing in Seattle: The Effects on Location and Type of Crime(2017-05) Sidebottom, ChristopherExisting literature generally acknowledges that crime is not random and dispersed across different areas, but instead crimes cluster at specific locations. While there are extensive studies covering the effect predictive policing has on crime rates, there are only a handful of researchers studying the effects on location and type of crime. Using a quasi-experimental research design for identification, estimation, and inference of treatment effects at a designated cutoff, this project examines Seattle Police Department’s implementation of predictive policing technology and its effects on precincts and types of crime throughout the city. The research suggests that the North, Southwest, and West precincts saw decreases in the number of reported crime incidences while serious crimes such as burglary and homicide saw overall reductions. The results of this project provide support for the city-level deployment of predictive policing programs specifically targeting high priority locations and types of crimes.Item A Flaw in the Federal Adult Education Funding Formula: Academic Gains and English Language Learners(2017-08) Judd, Amy ElizabethExisting research in the field of adult basic education diverges between transformative learning theory, which focuses on how student growth is accomplished in the classroom, and human capital theory, where adult education is viewed as an investment in a strong economy. US adult education programs are funded by federal legislation intended to create a strong workforce. Grant-funded programs are charged with serving adults deficient in the basic skills of literacy and numeracy or lacking a high school diploma, as well as adults who are limited in English language proficiency. Yet, the federal funding formula for state-level allocations has been historically based on Census calculations of adults lacking a high school diploma, and ignores those who do not speak English well, despite the expectation for grant-funded programs to serve both populations. In states serving large numbers of adults with limited English proficiency, programs struggle to meet performance requirements for student educational gain. The findings in this paper indicate that a better-aligned funding formula could more equitably distribute adult academic gains in each state, a matter of importance as US policymakers struggle to find common ground on issues of immigration, diversity, and upskilling the American workforce.Item Water Conflict Revisited: Fresh Water Scarcity as a Key Predictor of Contemporary Armed Conflict(2017-08) Feldman, AmyFor over 30 years, scholars have investigated the direct relationship between fresh water scarcity and armed conflict using a wide variety of analytical techniques. However, this body of literature has yet to provide a comprehensive empirical analysis that supports such a relationship for both interstate and intrastate conflicts. The ensuing report fills in the gaps of the existing discourse by closely reassessing the variables under consideration and employing a cross-sectional, time-series analysis of 172 states across the globe. The results from numerous negative binomial regression tests provide evidence supporting a statistically significant positive relationship between water scarcity and armed conflict; states having lower population percentages with access to improved water sources experience more instances of armed conflict – both interstate and intrastate. These findings prompt the conclusion that water scarcity is a significant predictor of armed conflict. As fresh water resources become increasingly limited across the globe, this study will continue to gain relevance, offering evidence to inform decisions about armed-conflict prevention in the international community.Item Privacy Public Opinion: Conflicted in the Current Cybersecurity Environment(2017-08) Bess, Jonathan C.Privacy public opinion is conflicted in the current cybersecurity environment. As the world becomes more interconnected in the digital realm, there is a struggle between information sharing versus the protection of that information. People are exposing more personal data for business, commerce, health and social purposes. This data is also increasingly under attack. Analysis of the number and types of privacy data breaches shows the cybersecurity environment is rapidly changing. This paper examines the relationship between public opinion on privacy as related to online habits, trust in institutions and beliefs about future cybersecurity attacks in the current cybersecurity environment. Statistical analysis of a 2016 survey covering all fifty states identified the most important predictors of privacy concerns. These were online account use, confidence in institutions and social media use. This research examining individuals’ privacy expectations, fears, and desire for security for their personal information provides useful data to influence future privacy and cybersecurity policy formulation.Item Predictive Analysis of Long-Term Risk Factors of Incarceration for At-Risk Youth(2017-08) Mason, KathleenThe use of predictive analytics to prevent crimes, or predictive policing, is increasingly used by governments as part of criminal justice and law enforcement strategies today. Broadening the application of predictive analytics to encompass primary prevention strategies better informs government policy by leveraging the additional dimension of identifying risk factors that predispose youth to incarceration. To predict incarceration, a decision tree model with 72% accuracy was developed using data from the Prevention Program, a longitudinal intervention conducted on 900 first grade students in urban Baltimore Public Schools in 1993. A K-means clustering model was applied to the population to identify three archetype profiles: females, adapted males, and maladapted males. Overall classroom behavior, authority acceptance, and overall behavioral problem contributed most to the clusters. Results show that peer-rated and teacher-rated behavioral factors primarily influenced both predictive models. This indicates that peers and teachers are a valuable resource for identifying at-risk youth.Item Perceived Discrimination and Racial Health Disparities: The Association of Race, Health Care Coverage and General Health on Perception of Discrimination(2017-08) Wallace, Robyn ClemonsPrior research acknowledges that racial health disparities are a challenge faced in public health. While the association between race, discrimination and health outcomes has been evaluated, this study explored perceived race-based discrimination and its association with health care coverage and self-evaluated general health. Multivariable logistic regression was conducted to examine if race, health care coverage status, and general health impact perceptions of an individual’s health care experience adjusting for age, gender, income, education attainment, and state. Analyses found that race - specifically self-identifying as Black, proved as a significant indicator for perceived discrimination while having poor general health and lacking health insurance coverage were both associated with increased odds and strong statistical relation to perceived discrimination regardless of race/ethnicity. Evidence from this research suggests that race and behavioral risk factors influence perceived bias and may further substantiate causal effects of racial health disparities.Item Who Visits National Parks? The Effect of Changing Local Demographics on National Park Visitorship(2017-08) Mealy, MaxDuring a two-decade general decline in visits to U.S. national parks during the 1990s and 2000s, annual visits to one-third of national parks actually increased. Previous research shows that park attendance varies by race, ethnicity, age, income, and education. This paper examines whether shifting demographics in the regions surrounding each national park explain historical fluctuations in visits. A linear fixed-effects model is used to estimate whether changes to these demographic indicators in the 100 miles surrounding national parks impacted visitation. The study found that local demographics had a statistically significant effect on park visitation and explained nearly half of year-to-year fluctuations in visits within each park. The effect of a change in local population on park visits was far smaller for African-American and Hispanic populations than white populations, suggesting that the National Parks System will face further challenges as the U.S. continues to become more diverse.Item Less Traditional, Less Success: The Negative Effect of Nontraditional Students on Community College Graduation Rates(2017-12) Dana, SamanthaCommunity colleges enroll 40% of all undergraduates and 60% of community college students are independent for financial aid purposes. Independent students, with a number of nontraditional traits, are increasing as high school graduate numbers dwindle in large parts of the country. However, the presence of nontraditional students as an institutional characteristic, and its effect on graduation rates, has not been previously studied quantitatively or at scale. Using data from the US Department of Education’s College Scorecard, regression analysis found a substantial and statistically significant negative effect of a college’s independent student percent on its graduation rate. This effect of between -12.5% and -25.2% remained after holding other previously identified variables constant and examining the interaction between independent percent and part-time attendance percent. These findings suggest that one or more obstacles unique to nontraditional students must be identified and remediated to increase graduation rates.Item Fraccidents: The Ostensible Link Between Oil and Gas Development and Car Accidents in Post-Shale Boom Texas Counties(2017-12) Benitez, RichardNew developments in the exploration of unconventional Oil and Gas (O&G) resources have become an energy industry trend. Nevertheless, there are underlying environmental and socio-economic impacts attributed to “fracking”, which could strain public resources and local transportation networks. From 2012 to 2016, a quarter-fold increase in the number of producing wells occurred simultaneously with a 29 percent increase in total car crashes as well. This study explores the purported link between O&G development and car crashes using Texas county-level panel data. Despite this anticipated relationship, the results presented a tenuous relationship between the two. However, the overall magnitude of the relationship between O&G development and car crashes improves upon the existing literature. The research also maintains that there is still an emerging opportunity for future scholarship and policy formulation regarding O&G development and its residual impacts on public safety and quality of life among other communities of interest.Item Identifying Intentionally Duplicative Public Comments Submitted to Proposed Federal Rules(2017-12) Armour, Karin M.Since the public commenting process for proposed federal regulations became primarily web-based, the number of rules receiving extremely high comment volumes has increased substantially; raising concerns about whether computer-generated comments designed to appear as if they represent the input of ordinary citizens could be distorting the regulatory process. As one example, the Consumer Financial Protection Bureau's (CFPB's) Payday, Vehicle Title, and Certain High-Cost Installment Loans Proposed Rule ("Payday Rule") received over one million comments, many of which appear to be from individuals, but are highly similar in wording and structure. Using a sentence-level document feature matrix (DFM) to identify repeated phrases, this analysis found that nearly 70 percent of the reviewed comments were moderately to highly suspicious duplicates. Drawing on the characteristics of these duplicates, this paper presents practical alternatives for federal agencies to prevent and respond to similar risks against the regulatory commenting process in the future.Item Machine Learning and Civil War: Investigating Tree-Based Models for Predicting Intrastate Violence(2017-12) Meire, HilaireThis study’s aim is to improve the forecasting of civil war and examine the practical utility of using machine learning techniques in this effort. Specifically, this study investigates a variety of sampling methods used to construct useful models from imbalanced data, the algorithm used to construct these models, and which of the models built by previous scholars is the most useful for prediction when different sampling procedures algorithms are applied. This study finds that up-sampling and SMOTE sampling generally improve model performance, that tree-based ensemble methods generally perform significantly better than logistic regression and that of these ensemble methods Extreme Gradient Boosting generally performs the best, and that the previous model constructed by Collier & Hoeffler performs extremely well, especially when combined with sampling procedures and tree-based ensemble methods.Item Responsiveness to Citizen Input: Topic Model Analysis of Public Comments to the San Francisco Police Commission(2017-12) Wollard, Carroll W. IIIPolice commissions are uniquely positioned to funnel critical issues raised by citizens to police departments, thereby increasing accountability and potentially improving police/community relations. However, no empirical study to date has analyzed the responsiveness of a civilian policing oversight entity to the voiced needs and concerns of its local community. This paper details a dictionary-based topic model analysis conducted on the minutes from the last 20 years of San Francisco Police Commission (SFPC) meetings. Across the time period, the San Francisco community voiced issues related to crime, accountability, and community most commonly at meetings. Further analysis using a logit regression with a distributed lag model indicated public comment on a topic was strongly associated with the topic being discussed by the SFPC at the same meeting. However, SFPC discussion of the topics voiced by the public waned in subsequent meetings. The results suggest a potential failure of the SFPC to meaningfully act on the concerns raised by the public.Item An Improved Index for Measuring Precinct-Level Political Ideology in California(2017-12) Bradford, DavidDespite California’s reputation as a solidly liberal state, there exist deep regional and neighborhood-level divisions in political ideology among voters. Factor analysis has been used in previous research to formulate an index of precinct-level ideology scores in California, based on the results of multiple ballot initiatives. However, the previous research (a) was conducted five years ago and measured a political landscape that has since changed considerably, and (b) used just two factors to form the precinct scores. The research here uses three factors to develop an improved index based on 2016 ballot initiative results. We find that California has grown more liberal overall and more polarized regionally. We also find that the new ideology index is highly predictive of 2016 presidential vote, and that Hillary Clinton’s support relative to Donald Trump’s slightly exceeded the expectations set forth by corresponding precinct ideology scores, meaning Clinton was more popular relative to Trump than the voters’ ideology would otherwise indicate. The new ideology index illuminates the underlying beliefs and values of the California electorate at a granular level, helps us understand how those beliefs relate to presidential preferences, and has the potential to help campaigns focus their outreach on receptive or persuadable precincts.
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