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Entrapment in Higher Education
No full textThe cost of a college education has risen exponentially over the past few decades and is reflected in student loan debt, which now exceeds $1.6 trillion in the United States alone (Federal Reserve Bank of New York, 2023). Undergraduate students may feel trapped in their degree program, as changing majors would result in additional time and money invested. Entrapment refers to the cognition of being stuck in an aversive or less-than-desirable situation. Often researched in connection with psychological wellbeing and suicidal ideation, recent studies have begun to explore entrapment in the workplace and amongst college students. This study explores entrapment among undergraduate college students enrolled in four-year colleges and universities in the United States, and examines possible associations between entrapment, academic major satisfaction, and scores on the planned happenstance career inventory (PHCI). Statistical analyses were run using data from 393 U.S. undergraduate students. Results indicated significantly higher entrapment among amongst students attending public universities, non-binary and transgender students, and students from low socioeconomic status backgrounds (RQ1), significant negative correlations between academic major satisfaction and entrapment (RQ2), and significant negative correlations between scores on the PHCI and entrapment (RQ3). Implications indicate the need for continued career counseling and exploration with college students. Limitations and future directions are discussed
Preventing Wrongful Convictions: Assessing Identification Evidence in the Digital Age
No full textAbstractWhile wrongful convictions may have a higher profile in the USA (given, among other factors, that the death penalty is still prevalent in that country and so the consequences of wrongful convictions are more severe), they are a significant concern in Canada as well. Faulty identification evidence has been implicated in wrongful convictions in Canada and so the forensic science that explicates when such evidence is reliable and when it is not has general importance for the criminal justice system and particular importance in the prevention of wrongful convictions. In recent years, the introduction and growth of social media have added further contaminants potentially affecting identification evidence which have, increasingly, been recognised by the courts. However, the full implications of social media’s deleterious effects in this area are not yet fully understood. More forensic, scientific study of the impact of social media on the reliability of identification evidence is accordingly warranted
The Impacts of Climate and Land Use Change on Mojave Desert Tortoise (Gopherus agassizii) Habitat Suitability and Landscape Genetic Connectivity
Get PDFThe Mojave desert in the southwestern United States faces a multitude of anthropogenic stressors including urbanization, population growth, solar energy development, expansion of transportation infrastructure and military training, as well as climate change that has impacted the region through habitat fragmentation and altered precipitation and temperature regimes. The Mojave desert tortoise is a species that persists on this landscape despite these impacts that could influence its long-term population densities, distributions, and connectivity.A fundamental goal of conservation prioritization is understanding the distribution of suitable habitat and maintaining connected landscapes between these habitats to ensure species can adapt to changes in their environments. Species distribution models identify regions of suitable habitat based on statistical modeling relating location data for the species to environmental variables that influence the distribution of the species. Examining how landscape features, specifically landscape composition and configuration, interact with microevolutionary processes such as gene flow helps identify which landscape features facilitate or limit gene flow and subsequently connectivity for a species. In this dissertation I sought to understand how the compounded effects of land use and climate change would impact habitat suitability and landscape connectivity at multiple temporal and spatial scales for the tortoise using various spatial and genetic tools. In chapter 1 I created a sampling design to guide targeted field efforts to obtain location and genetic data focused on under-surveyed edge regions of the tortoise’s range. I used this sampling design to obtain new genetic samples and used the new dataset to determine the efficacy of my initial design as well as examine whether my new samples represented new climatic niches. In chapter 2 I built a range-wide habitat suitability model for the tortoise and forecasted this model to climate and land use change scenarios. I also explored the influence of scale by building regional habitat suitability models and forecasting these models. I found that precipitation, temperature, and soil variables influence habitat suitability at range-wide scales and the direction of these relationships changed at the regional scale. Forecast models predicted widespread loss of tortoise habitat under all future scenarios, with the highest net change in habitat across critical habitat units for the species, and least net change across military bases. Habitat was shifted northward over time, with the southern edge losing the most amount of habitat by the worst-case climate and land use scenarios in 2098. In chapter 3 I used a range-wide genomics dataset to estimate population structure and to build habitat-based connectivity models using isolation-by-resistance (IBR) approaches at various temporal scales. I found that as habitat availability declined in the southern edge of the range, there was a concomitant loss of connectivity, and that connectivity was also gained in the northern edge of the range. I used comparative modeling in a maximum likelihood population effects (MLPE) framework and found that IBR based metrics were the best predictors of range-wide connectivity, indicating that habitat features on the landscape drive genetic differentiation and gene flow for the tortoise. Overall, this work creates a novel sampling design methodology as well as identifies the impacts of climate and land use on tortoise habitat and connectivity using multiple approaches. This research identifies specific tortoise habitat and connective corridors, in vulnerable regions such as the southern and central range, that should continue to be protected to ensure persistence of the species currently as well as into the future
Data-Driven Analysis and Topology-Aware Learning of Phasor and Waveform Measurements for Enhanced Situational Awareness in Power Systems
No full textPower grids are evolving with the integration of more renewable generation resources and different types of loads. This shift introduces new types of challenging events, oscillations, and controller responses, in addition to typical faults and outages. Additionally, phasor and waveform measurement devices are being increasingly used, measuring system variables such as voltage and current at a high reporting rate across the grid. This provides opportunities to enhance modern power grid monitoring during events and grid responses. Therefore, a fundamental question is how to analyze this valuable recorded data for practical power system monitoring and achieve better situational awareness. This dissertation is concerned with data-driven analysis of events and operational changes of assets by using statistical analysis, signal processing, and topology-aware learning methods. Events, abrupt changes and oscillations in power systems create specific signatures on the measurement signals, so effectively analyzing them helps enhance event detection, clustering, classification, and localization of their sources. These attempts, relying on the proposed methods in this dissertation, such as graph-based learning, short-time modal analysis, and statistical wavelet-based studies, can provide energy utilities with insight into the ongoing conditions in the power system. This can enable them to take proper actions, predict grid responses, and prevent failures at early stages, ensuring reliable and sustainable energy for people
Do Regional Habitat Models Outperform a Single-model Approach for Resource Selection at a Population Scale? A Case Study with Mule Deer in Nevada
No full textEffective conservation and management of ungulate species requires characterization of resource availability, selection, and use. Mule deer ( Odocoileus hemionus ) in the Great Basin are experiencing population reductions that are generally thought to be driven by declines in their preferred sagebrush-dominated habitats. In many parts of the Great Basin, sagebrush habitats are being rapidly lost or degraded due to wildfire, energy development, mining, anthropogenic development, climate change, and overgrazing. Robust models of resource selection by mule deer allow wildlife managers to make more informed decisions about habitat protection and permitting for development projects. We used machine learning (random forest) to evaluate patterns of habitat selection at the population level (second order) during summer by GPS-collared mule deer ( n = 630) across northern Nevada. We divided our study area into four ecologically distinct regions. We compared two alternative modeling approaches: a "region-specific" modeling approach, in which we fit separate resource selection models for each region (thereby accommodating distinct patterns of resource selection within each region), and an "all-regions'' modeling approach, in which we fit a single model of mule deer habitat selection for our study region (assuming similar resource patterns across all four regions). The all-regions model outperformed the regional models in cross-validation, indicating that patterns of selection of resources by mule deer were similar across northern Nevada. Our models indicated that mule deer favored summer habitats near perennial water sources, with higher cover of perennial grasses and forbs, less bare ground, and cooler temperatures than expected on the basis of available resources. Our research is important for mule deer conservation by comparing model performance of summer resource selection at the landscape level (second order), which highlights areas of conservation need from future anthropogenic alterations within the Great Basin
Democracy's Wild Side: Using LocalView to Understand Municipal Council Discourse on Wildlife
No full textThis project emerged as a culmination between Dr. Johnson’s and my interests. Dr. Johnson wanted to explore how city councils operate, whereas I was intrigued by how they engage with wildlife. We combined these ideas to create the question for this research project: How do city councils address wildlife? The purpose of this project is to understand the way in which issues regarding wildlife – and more generally sustainability – are discussed on the local government level by city councils, including what issues are most pressing and how cities implement solutions. As we approached this topic, we began with literature review. We explored efforts that municipalities across the globe have made to address environmental and sustainability concerns. We then moved to analyzing local government city council meeting agendas, organizing them by topics of interest. Next, we created a list of key words that we predicted would appear in the agendas, referencing our literature review and the topics that cities seem most likely to address in relation to wildlife. We are interested in discovering how often cities address sustainability issues, if at all, and what actions they take, if any. We are currently in the process of collecting and analyzing this data. We hope this data can be used to understand the process by which wildlife regulation and sustainability is implemented in order to improve the way that city councils approach this topic
bodymind: exploring a trans disabled present
No full textThis paper explores the relationships between transgender and disabled identity through the lenses of art and language, examining my series of 12 portrait-style paintings with adjoining components of hand-built pedestals, canvases, and benches made out of laminated wood and unraveled trans tape. It functions to create conversation about transgender and/or disabled experiences through narratives of language and pleasure to honor transgender and disabled people while they are still living, providing a sense of community and context, as well as a refutation of narratives that exclude and diminish transgender and disabled people.The Nevada Undergraduate Research Awar
Attention-Enabled Reinforcement Learning for Control of Scalable Multi-Agent Systems
Get PDFMulti-agent reinforcement learning has been the subject of considerable interest and effort for its potential as a means of specifying behavior policies for multi-agent systems. Specifically, on-policy algorithms based on gradient estimation have achieved state-of-the-art performance on end-to-end control problems once thought beyond the scope of machine learning methods. In seeking to apply the benefits of MARL to practical control of physical autonomous systems, we must begin to account for three factors: (1) the presence of other autonomous elements in the environment configuration space, which may or may not be amenable to coordination; (2) non-idealities in sensing the configuration of the environment (e.g. locality and limited observability); and (3) variability in the number of sensed dynamical elements. The attention head, a relational ML structure originally designed for extraction of abstract natural language features, is structurally well suited to addressing these challenges. This work presents a systematic argument and framework for the use of attention as an input layer to enable learning of neural policy models in changing multi-agent environments which are not well-suited to other representations. In benchmark physical simulations, it is shown that such models achieve competitive performance on cooperative and mixed cooperative/competitive MAS control tasks as the agent cohort is arbitrarily changed. Prospective advantages of attention-based architectures for physical autonomous systems in select applications are discussed, as well as drawbacks associated with explainability and potential for emergent behavior
Three Essays in Applied Economics
No full textThis dissertation consists of three essays on the theory of interest rate via the overlapping generation model, developmental economics, and behavioral response to taxation. The first essay aims to investigate how a shift in income from young age to old age would change the equilibrium path for the economy. The second essay explores and estimates the connections between international remittances and the level of household poverty in Vietnam using the Vietnamese Household living Standard Survey from 2004 to 2016. In the third essay, we conduct the first meta-analysis of the literature estimating tax elasticity of border sales. In the first chapter, the model of Banerjee and Pingle (2023) is extended here in the same way Gale (1973) extended the Samuelson (1958) model. Rather than all income being earned in young age, the allocation of labor time is parameterized, so a fraction of labor allocated to young age versus old age can be varied. We find that shifting income from young age to old age does not impact the path of capital, which implies it does not affect the paths for output, the real wage, the capital rental rate nor real interest rate. The shift does decrease saving and decrease the share of saving allocated to the bubble asset. The steady state utility level of consumers is maximized when all income is earned in young age. In the second chapter, I investigate the relationship between international remittances and poverty in Vietnamese households. Utilizing the Vietnamese Households Living Standard Surveys from 2004 to 2016, our probit models indicate that international remittances reduce the likelihood of a household being in poverty by 11 to 14 percentage points. Furthermore, using instrumental variables, a bivariate analysis estimates confirm that the impact on poverty reduction is more pronounced for remittances originating from oversea compared to domestic remittances. This finding holds significant implications for policymakers, providing insights into the effective use of remittances and foreign labor migration as strategies to alleviate poverty in Vietnam. In the third essay, we conduct the first meta-analysis of the literature estimating tax elasticity of border sales. When nearby regions have different tax rates, residents may travel to shop in the lower tax rate region. The extent of this activity is captured by the tax elasticity of border sales (TEBS). We collect 749 estimates of TEBS reported in 60 studies, and conduct the first meta-analysis of this literature. We show that the literature is prone to selective reporting: positive estimates are systematically discarded. Sales of food, retail and fuel are more elastic compared to sales of tobacco and other individual 'sin' products. Cross-border shopping is more prominent in the US - compared to Europe and other countries