Using Quantitative Methods to Explore Political Leverage, Trade Policy, and Food Security: A Case Study of the Middle East

This dissertation explores why some states consistently secure food imports at prices higher than the world market price, thereby exacerbating food insecurity domestically. I challenge the idea that free market economics alone can explain these trade behaviors, and instead argue that states take into account political considerations when engaging in food trade that results in inefficient trade. In particular, states that are dependent on imports of staple food products, like cereals, are wary of the potential strategic value of these goods to exporters. I argue that this consideration, combined with the importing state’s ability to mitigate that risk through its own forms of political or economic leverage, will shape the behavior of the importing state and contribute to its potential for food security. In addition to cross-national analyses, I use case studies of the Gulf Cooperation Council states and Jordan to demonstrate how the political tools available to these importers affect their food security. The results of my analyses suggest that when import dependent states have access to forms of political leverage, they are more likely to trade efficiently, thereby increasing their potential for food security.

SHIFTING SCALES, ADJUSTING LENSES: A FRAMEWORK FOR INVESTIGATING BALTIMORE’S URBAN VACANCY

This thesis addresses contemporary gaps of vacancy within literature by using qualitative and quantitative methods and tools to determine the quantity, location, and interspatial relationships of vacant buildings and lots located in Baltimore Maryland. Spatial analyses were conducted to answer three questions of vacancy: 1) how many vacant lots and buildings exist, 2) whether there are spatial patterns of vacancy, such as clustering around geographic locations or within watersheds, and 3) how to prioritize intervention opportunities that respond to the city's larger issues? Using the city’s vacant lot and building data-sets, two concepts emerged from these investigations. First, Utilized Landscapes as a classification system that identifies lands that serve a function but have un-traditional qualities that make them susceptible to being labeled “vacant.” Second, the development of Transitional Zones, geographical areas with a high density of vacant buildings or lots that should be prioritized.

Integrating Environmental Justice and Social-Ecological Resilience for Successful Adaptation to Climate Change: Lessons from African American Communities on the Eastern Shore of the Chesapeake Bay

This research concerns the conceptual and empirical relationship between environmental justice and social-ecological resilience as it relates to climate change vulnerability and adaptation. Two primary questions guided this work. First, what is the level of resilience and adaptive capacity for social-ecological systems that are characterized by environmental injustice in the face of climate change? And second, what is the role of an environmental justice approach in developing adaptation policies that will promote social-ecological resilience? These questions were investigated in three African American communities that are particularly vulnerable to flooding from sea-level rise on the Eastern Shore of the Chesapeake Bay. Using qualitative and quantitative methods, I found that in all three communities, religious faith and the church, rootedness in the landscape, and race relations were highly salient to community experience. The degree to which these common aspects of the communities have imparted adaptive capacity has changed over time. Importantly, a given social-ecological factor does not have the same effect on vulnerability in all communities; however, in all communities political isolation decreases adaptive capacity and increases vulnerability. This political isolation is at least partly due to procedural injustice, which occurs for a number of interrelated reasons. This research further revealed that while all stakeholders (policymakers, environmentalists, and African American community members) generally agree that justice needs to be increased on the Eastern Shore, stakeholder groups disagree about what a justice approach to adaptation would look like. When brought together at a workshop, however, these stakeholders were able to identify numerous challenges and opportunities for increasing justice. Resilience was assessed by the presence of four resilience factors: living with uncertainty, nurturing diversity, combining different types of knowledge, and creating opportunities for self-organization. Overall, these communities seem to have low resilience; however, there is potential for resilience to increase. Finally, I argue that the use of resilience theory for environmental justice communities is limited by the great breadth and depth of knowledge required to evaluate the state of the social-ecological system, the complexities of simultaneously promoting resilience at both the regional and local scale, and the lack of attention to issues of justice.

The Demobilized Body: Transgressions of Personal Space and Political Participation

Grounded in the intersection between gender politics and electoral studies, this dissertation examines the demobilizing effects of violations of personal space (in the form of domestic violence, control over mobility, emotional abuse, and sexual harassment) on the propensity to vote. Using quantitative methods across four survey datasets concerning Lebanon, the United States, Morocco, and Yemen, this research concludes that cross-regionally, familial control over mobility reduces the propensity to vote among women. Conversely, mechanisms of empowerment such as education and employment increase the propensity to vote.

Quantitative and Qualitative Trade-Off Analysis of Drowsy Driver Detection Methods: Single Electrode Wearable EEG Device, Multi-Electrode Wearable EEG Device, and Head-Mounted Gyroscope

Drowsy driving impairs motorists’ ability to operate vehicles safely, endangering both the drivers and other people on the road. The purpose of the project is to find the most effective wearable device to detect drowsiness. Existing research has demonstrated several options for drowsiness detection, such as electroencephalogram (EEG) brain wave measurement, eye tracking, head motions, and lane deviations. However, there are no detailed trade-off analyses for the cost, accuracy, detection time, and ergonomics of these methods. We chose to use two different EEG headsets: NeuroSky Mindwave Mobile (single-electrode) and Emotiv EPOC (14- electrode). We also tested a camera and gyroscope-accelerometer device. We can successfully determine drowsiness after five minutes of training using both single and multi-electrode EEGs. Devices were evaluated using the following criteria: time needed to achieve accurate reading, accuracy of prediction, rate of false positives vs. false negatives, and ergonomics and portability. This research will help improve detection devices, and reduce the number of future accidents due to drowsy driving.

Developing Quantitative Methodologies for the Digital Humanities: A Case Study of 20th Century American Commentary on Russian Literature

Using scientific methods in the humanities is at the forefront of objective literary analysis. However, processing big data is particularly complex when the subject matter is qualitative rather than numerical. Large volumes of text require specialized tools to produce quantifiable data from ideas and sentiments. Our team researched the extent to which tools such as Weka and MALLET can test hypotheses about qualitative information. We examined the claim that literary commentary exists within political environments and used US periodical articles concerning Russian literature in the early twentieth century as a case study. These tools generated useful quantitative data that allowed us to run stepwise binary logistic regressions. These statistical tests allowed for time series experiments using sea change and emergency models of history, as well as classification experiments with regard to author characteristics, social issues, and sentiment expressed. Both types of experiments supported our claim with varying degrees, but more importantly served as a definitive demonstration that digitally enhanced quantitative forms of analysis can apply to qualitative data. Our findings set the foundation for further experiments in the emerging field of digital humanities.

Working with Student Teachers: A Mixed Methods Study to Examine the Roles and Self-Identified Dispositions of Cooperating Teachers

A critical component of teacher education is the field experience during which candidates practice under the supervision of experienced teachers. Programs use the InTASC Standards to define the requisite knowledge, skills, and dispositions for teaching. Practicing teachers are familiar with the concepts of knowledge and skills, but they are less familiar with dispositions. Practicing teachers who mentor prospective teachers are underrepresented in the literature, but they are critical to teacher preparation. The research goals were to describe the self-identified dispositions of cooperating teachers, identify what cooperating teachers consider their role in preparing prospective teachers, and explain challenges that cooperating teachers face. Using a mixed methods design, I conducted a quantitative survey followed by a qualitative case study. When I compared survey and case study data, cooperating teachers report possessing InTASC critical dispositions described in Standard 2: Learning Differences, Standard 3: Learning Environments, and Standard 9: Professional Learning and Ethical Practice, but not Standard 6: Assessment and Standard 10: Leadership and Collaboration. Cooperating teachers assume the roles of modeler, mentor and advisor, and informal evaluator. They explain student teachers often lack skills and dispositions to assume full teaching responsibilities and recommend that universities better prepare candidates for classrooms. Cooperating teachers felt university evaluations were not relevant to teaching reality. I recommend modifying field experiences to increase the quantity and duration of classroom placements. I suggest further research to detail cooperating teacher dispositions, compare cooperating teachers who work with different universities, and determine if cooperating teacher dispositions influence student teacher dispositions.

SEMIPARAMETRIC METHODS IN THE ESTIMATION OF TAIL PROBABILITIES AND EXTREME QUANTILES

In quantitative risk analysis, the problem of estimating small threshold exceedance probabilities and extreme quantiles arise ubiquitously in bio-surveillance, economics, natural disaster insurance actuary, quality control schemes, etc. A useful way to make an assessment of extreme events is to estimate the probabilities of exceeding large threshold values and extreme quantiles judged by interested authorities. Such information regarding extremes serves as essential guidance to interested authorities in decision making processes. However, in such a context, data are usually skewed in nature, and the rarity of exceedance of large threshold implies large fluctuations in the distribution's upper tail, precisely where the accuracy is desired mostly. Extreme Value Theory (EVT) is a branch of statistics that characterizes the behavior of upper or lower tails of probability distributions. However, existing methods in EVT for the estimation of small threshold exceedance probabilities and extreme quantiles often lead to poor predictive performance in cases where the underlying sample is not large enough or does not contain values in the distribution's tail. In this dissertation, we shall be concerned with an out of sample semiparametric (SP) method for the estimation of small threshold probabilities and extreme quantiles. The proposed SP method for interval estimation calls for the fusion or integration of a given data sample with external computer generated independent samples. Since more data are used, real as well as artificial, under certain conditions the method produces relatively short yet reliable confidence intervals for small exceedance probabilities and extreme quantiles.

MULTI-UNIT ACCIDENT CONTRIBUTIONS TO U.S. NUCLEAR REGULATORY COMMISSION QUANTITATIVE HEALTH OBJECTIVES: A SAFETY GOAL POLICY ANALYSIS USING MODELS FROM STATE-OF-THE-ART REACTOR CONSEQUENCE ANALYSES

The U.S. Nuclear Regulatory Commission implemented a safety goal policy in response to the 1979 Three Mile Island accident. This policy addresses the question “How safe is safe enough?” by specifying quantitative health objectives (QHOs) for comparison with results from nuclear power plant (NPP) probabilistic risk analyses (PRAs) to determine whether proposed regulatory actions are justified based on potential safety benefit. Lessons learned from recent operating experience—including the 2011 Fukushima accident—indicate that accidents involving multiple units at a shared site can occur with non-negligible frequency. Yet risk contributions from such scenarios are excluded by policy from safety goal evaluations—even for the nearly 60% of U.S. NPP sites that include multiple units. This research develops and applies methods for estimating risk metrics for comparison with safety goal QHOs using models from state-of-the-art consequence analyses to evaluate the effect of including multi-unit accident risk contributions in safety goal evaluations.