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The Connection Between Fragmentation And Traffic Stops
No full textThroughout the United States, there are hundreds of metropolitan areas. For myriad reasons, the number of local governments within each metropolitan area varies. Some scholars argue that having too many local governments leads to inefficiencies and inequities for the metropolitan area as a whole and for its central city in particular (e.g., Wood, 1958; Dreier et al., 2014). Others maintain the opposite. They contend that having more local governments leads to greater competition between municipalities for citizens and businesses. This, in turn, keeps service costs low, leads to lower taxes, and provides greater choice for citizens in terms of places to live and taxes paid for services provided (e.g., Tiebout, 1956; Schneider, 1989). Whatever stance one takes on the matter, municipal fragmentation – defined here as the number of local governments within a metropolitan area – has an impact on the lives of citizens throughout each metropolitan area in the U.S.
Further, within each metropolitan area, there are numerous local law enforcement agencies providing a needed and valuable service – protecting the citizens of their jurisdiction and enforcing the jurisdiction’s laws. As with the number of local governments, there is variation in the number of local police departments serving citizens within each metropolitan area. I define this concept as police jurisdictional fragmentation.
My research focuses on municipal fragmentation and police jurisdictional fragmentation and examines whether they have an impact on traffic stops within a metropolitan region and/or any bearing on racial disparities in said traffic stops. By looking into the traffic stop patterns and disparities, my research helps paint a fuller picture of the everyday experiences of metropolitan area residents in the United States, experiences that shape how they view the world and how they interact with it. It also provides a unique view of fragmentation’s effect on equity in public services
Glucose-Responsive Insulin For The Treatment Of Diabetes
No full textThe treatment of Type 1 diabetes (T1D) presents significant challenges, as patients rely entirely on external insulin to regulate blood glucose levels. Conventional insulin therapies, often require frequent administration and carry a substantial risk of hypoglycemia. Current insulin infusion pump system also needs frequent calculation and input of estimated meal calories. In contrast, glucose-responsive insulin (GRI) systems offer a promising solution by mimicking the body\u27s natural insulin regulation, releasing insulin dynamically in response to glucose levels. This dissertation introduces a novel GRI delivery system based on a copolymer containing human recombinant insulin. At low blood glucose levels, the copolymer insulin remains within the formulation, minimizing systemic glycemic effects. At high blood glucose levels, the copolymer insulin is triggered to release from the formulation, enabling glucose-responsive insulin release and effective glycemic control. This dissertation focused on three GRI formulations. An implantable GRI formulation was developed to target long-term diabetes correction, demonstrating effective glucose responsiveness in both small and large animal models. Additionally, an injectable GRI formulation for subcutaneous administration was developed, exhibiting improved efficacy, ease of use, and dose potency, as validated in diabetic mice and Göttingen minipigs. Finally, a pilot oral GRI capsule prototype was developed to overcome gastrointestinal barriers. This oral formulation prototype demonstrated glucose responsiveness and stable pharmacokinetics in diabetic rats, offering a potential non-invasive alternative to traditional insulin delivery methods. A key innovation of this GRI system lies in the tunability of the copolymer insulin’s glucose responsiveness. This enables precise insulin release tailored to individual patient needs, offering a path toward personalized diabetes management. Together, these advancements represent a significant step forward in the development of safer, more effective, and patient-friendly insulin therapies for T1D
Engaging Ghana’s Basic School Mathematics Teachers In Relational Conceptual Change Teaching: A Researcher -Teachers Collaborative Inquiry
No full textThis dissertation explores Ghanaian Basic School mathematics teachers\u27 concerns and professional development needs to implement the Standards-Based Mathematics Curriculum (SBMC). The study synthesizes findings from three distinct yet interconnected research articles, each offering a nuanced perspective on teacher readiness and instructional practices in SBMC implementation.The first article employs a mixed-methods approach, combining the Stages of Concern Questionnaire (SoCQ) responses from 87 teachers and qualitative interviews with 18 participants. It identifies self and impact stages as predominant concerns, emphasizing the need for professional collaboration and systemic reflection to support SBMC adoption. Cross-sectional analyses reveal no significant demographic influences on teachers’ concerns, underscoring their universal nature across varied profiles. The second article evaluates the role of professional learning in equipping teachers for SBMC enactment through the Common Knowledge Construction Model (CKCM). This phase highlights collaborative inquiry, diversity, equity, and inclusion as pivotal to enhancing teachers\u27 conceptual understanding and classroom discourse. Data from workshops and follow-up reflections demonstrate shifts in teacher practices, including fostering student-centered learning environments and connecting curriculum content to lived experiences. The final article delves into the effectiveness of post-professional development interventions by examining classroom discourse quality using CKCM principles. Observations reveal notable improvements in teachers’ facilitation skills, increased engagement with formative assessments, and the integration of student ideas into instructional planning. The findings collectively advocate for equitable resource distribution, structured professional development, and reflective practices to address teachers\u27 concerns and advance effective mathematics education reforms in Ghana. Keywords: Standards-Based Mathematics Curriculum, Teacher Concerns, Professional Development, Classroom Discourse, Ghan
Evaluation Of Impacts And Drivers In Stream Ecosystems: Land Development, Nutrient Pollution, And Road Salt Exposure Through Responses In Benthic Macroinvertebrates
No full textBenthic macroinvertebrates are critical bioindicators that are sensitive to a range of environmental stressors, such as urbanization, nutrient enrichment, and salinization. These stressors can lead to shifts in community composition and a subsequent decline in ecosystem health, jeopardizing the integrity of fluvial systems. In this study, land use settings were compared with publicly available nitrogen (N) and phosphorus (P) data and integrated with benthic macroinvertebrate surveys to assess the impact of nutrient conditions on Michigan waterways over a 20-year period (2002-2021). This analysis aimed to explore how different land use settings influence the seasonal and annual concentrations of N and P in Michigan streams and how these nutrient levels affect benthic macroinvertebrate communities. Next, in-situ assessments of benthic macroinvertebrates were performed at twenty streams to evaluate community responses in response to available basal resources and riparian cover, using a watershed-scale land cover analysis. This study compared two distinct climate types: humid continental (southeastern Michigan) and tropical monsoonal (Puerto Rico). The focus was on sites impacted by development and agricultural land use, as well as those with varying riparian cover densities. This comparison allowed for an assessment of how anthropogenic disturbances and riparian cover affect benthic macroinvertebrate communities, considering their different roles in each climate effects. Under controlled experimental conditions, burrowing mayfly nymphs (Hexagenia spp.), were exposed to road salt to examine the effects of salinity on their behavior, physiology, feeding strategies and nutrient assimilation. Hexagenia spp. are commonly used in toxicity studies due to their presence being indicative of good water quality and/or habitat recovery. The study evaluated several parameters, including isotopic signatures (13C and 15N), survival rate, drift, and respiration responses across various experimental designs.
The main findings indicate that increased agricultural and developed land uses promote a rise of inorganic nitrogen (NO2 + NO3) and TP, which, in turn, drive changes in benthic macroinvertebrate communities. However, nutrients do not appear to be strongly correlated with land use and shifts in these communities at a state-level. Agricultural and land development disturbances result in the prevalence of more tolerant species assemblages, and more collectors-gatherers (e.g., chironomids and oligochaetes). Conductivity influences these assemblages, while riparian cover and higher drainage areas serve as less resilient features in temperate regions, although they are more resilient in tropical regions. Shifts in feeding strategies and respiration in Hexagenia suggest signs of recovery in freshwater systems, linked to increased tolerance of CaCl2 + Mg. This research highlights the importance of promoting the restoration and management of fluvial systems through three key actions: (1) identifying areas in need of stream assessment in Michigan, USA, (2) understanding how climate effects influence benthic macroinvertebrate assemblages in areas with similar riparian cover and anthropogenic disturbances, and (3) raising awareness about the harmful impacts of salt application, which adversely affects key bioindicators and triggers a cascade of effects throughout food web interactions
First-Year Writing And The Queer Pedagogy Of Dismantling
No full textThe realm of queer theory has many applications to pedagogical practices in compositionclasses, but it is largely misunderstood. Proponents of diversity, equity, and inclusion in college writing classes often see gender and sexuality as parallel to other dimensions of identity. This dissertation proposes a distinction between equity queer pedagogy and inquiry queer pedagogy. Equity pedagogy aims for explicit inclusion of students, faculty, and texts that express nonnormative sexuality. Inquiry pedagogy uses the insights of queer theory to explore, problematize, and challenge presumptions about student identity and pedagogical approach
Ecological Impacts Of Quagga Mussels On Yellow Perch And Their Morphological And Physiological Divergence Across Two North American Invasions
No full textQuagga mussels (Dreissena rostriformis bugensis) first invaded the Laurentian Great Lakes via ballast water discharge in the late 1980s and have since spread to cool, deep inland lakes and rivers from the Great Lakes to as far west as California. They have significantly altered nutrient cycling, reduced zooplankton biomass, and disrupted microzooplankton communities, impacting prey availability for planktivorous fish such as yellow perch (Perca flavescens). However, the impacts of quagga mussel veligers (free-swimming larvae) on fish that consume them remains poorly understood. Additionally, understanding morphological and physiological differences between geographically distinct quagga mussel populations is critical for deciphering invasion pathways and developing control strategies. This research aimed to: 1) determine how veligers affect yellow perch survival, growth, and diet in a laboratory setting; 2) assess diet preferences and feeding success of yellow perch in Lake Michigan, including the incidence of empty stomachs; and 3) compare morphology and physiological responses to stressors between adult quagga mussel populations in Lake Mohave, NV, (a recent invasion) and the Detroit River, MI (an older invasion). Laboratory experiments indicated that yellow perch larvae fed a veliger rich diet had reduced survival and lower growth compared to those fed Artemia nauplii. Field data showed that yellow perch preferentially consumed veligers when abundant but avoided them when native prey was more available. Smaller fish had higher rates of empty stomachs, suggesting feeding success is closely tied to fish size and may influence survival. This shift toward veliger consumption could exacerbate challenges like prey composition or availability, potentially hindering yellow perch recruitment success. Finally, adult quagga mussels from Lake Mohave and the Detroit River exhibited distinct morphological traits and physiological responses to cyanobacteria exposure. This research provides novel insights into the ecological impacts of quagga mussel veligers on yellow perch and demonstrates how distinct dreissenid populations may acclimate to local environmental conditions
The Ripple Effects Of Microaggressions: Understanding Employee Responses And The Moderating Role Of Racial Representation At Work
No full textDespite the advancement of research on microaggressions, their impact on employees’ emotional well-being and behavior remains unclear (Fattoracci & King, 2023). In response, I examine the associations between microaggressions, hurt feelings, and counterproductive work behaviors (i.e., withdrawal and production deviance). Additionally, I consider racial representation as a potential moderator. Drawing upon social identity theory, social categorization theory, and the Stressor-Emotion Model, I argue that microaggressions lead to hurt feelings, prompting employees to engage in counterproductive work behaviors as a coping mechanism (Tajfel & Turner, 1979; Tajfel et al., 1971; Spector & Fox, 2005). Furthermore, I argue that the positive indirect relationship between microaggressions and counterproductive work behaviors is likely to be weaker in organizations with greater racial representation. Results revealed that the relationship between microaggressions and hurt feelings was positive and significant. However, the positive indirect effect between microaggressions and withdrawal deviance through hurt feelings was nonsignificant. Interestingly, the positive indirect relationship between microaggressions and production deviance through hurt feelings was found to be significant. These findings underscore the importance of addressing emotional distress in the workplace, as unresolved hurt feelings can disrupt employees’ productivity. Additionally, the results revealed that racial representation did not moderate the relationship between microaggressions and hurt feelings, suggesting that the perception of diversity alone does not mitigate the negative impact of microaggressions
A Large Language Model-Based Approach To Detecting Sexism And Misogyny In Github Comments
No full textSexist and misogynistic behavior remains a significant barrier to inclusion in technical communities such as GitHub. Many developers initially join open-source projects, but experiences of microaggressions, dismissiveness, and subtle gender biases often drive them away, leading to high attrition, especially among minority groups. However, existing moderation tools—often limited to keyword filtering or simple binary classifications—frequently fail to detect such nuanced forms of harm. This study addresses a critical gap in existing moderation tools by introducing a fine-grained and interpretable classification framework.To achieve meaningful moderation, we aim to move beyond binary classification toward a deeper understanding of harmful behavior, identifying twelve distinct categories of sexist and misogynistic content in GitHub comments. Additionally, we investigate how different prompt design choices influence the performance of large language models (LLMs) in detecting subtle, context-dependent forms of harm. We collected a dataset of 11,007 GitHub comments and selected 1,422 representative examples that covered twelve behaviorally defined harm categories for evaluation. We then evaluated instruction-tuned LLMs (GPT-4o, LLaMA 3.3, and Mistral 7B) using a few-shot prompting pipeline, refining the prompts iteratively to improve classification accuracy. The final prompt design incorporated detailed category definitions, explicit output format constraints, confidence scores for each decision, and brief model explanations. We also explored parameter tuning—such as temperature, top-p, and max tokens—to improve classification accuracy. We assessed the models’ performance using precision, recall, F1-score, and Matthews Correlation Coefficient (MCC). Iterative prompt refinement led to significant improvements in classifying nuanced categories such as Discredit, Damning, and Victim Blaming, which were previously prone to misclassification. The best-performing configuration (Prompt 19 with GPT-4o) achieved an MCC of 0.4967, notably demonstrating a moderate correlation between predicted and actual classifications and showcasing the effectiveness of our approach in capturing subtle and context-sensitive harm. We also found that GPT-4o consistently outperformed the other models, although overall performance varied across model architectures, highlighting the importance of model selection in moderation tasks. Our results demonstrate that well-crafted prompts—grounded in clear, behavior-specific definitions and structured output formats—can substantially improve both the accuracy and interpretability of LLM-based content moderation. This approach provides a scalable and transparent framework for moderating harmful discourse in software engineering communities and offers practical design recommendations for deploying LLMs in real-world moderation scenarios