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How Mass Incarceration Has Destroyed African American Communities
Get PDFBeginning with the “Tough on Crime” movement of the 1970s, policies such as mandatory minimums, the War on Drugs, and the Three Strikes law have reinforced racial disparities in the criminal justice system. Multiple historical and systemic factors have contributed to the disproportionate imprisonment of African American individuals. This paper explores the long-term consequences of incarceration, including the erosion of family structures, the economic marginalization of affected communities, and the perpetuation of poverty and crime. The repercussions of parental incarceration on children and the challenges faced by formerly incarcerated individuals seeking reintegration into society are examples of the long-term consequences of the systemic increase in imprisonment of African American communities. Mass incarceration has functioned as a continuation of systemic racial oppression in the United States. There is an urgent need for policy reforms aimed at reducing racial disparities, investing in community-based rehabilitation, and addressing the root socioeconomic causes of crime
All Eyes on Me: Security and Preventative Measures in the Era of Shoplifting
Get PDFThe passing of CA bills ranging from AB 1779 to SB 1416, and Proposition 36 aims to combat a supposed rise in retail theft, particularly denoting the increase in organized retail theft. This research investigates the accuracy of mainstream narratives surrounding retail theft, focusing on the various security strategies adopted by major retailers—namely, Walmart and Target stores—in the San Francisco Bay Area. The study aims to analyze the different types of security (human and physical), and their efficacy, and to envision alternative strategies to address theft beyond the adoption of punitive security strategies. Using a visual ethnographic approach, supplemented with field observations, this study utilizes visual media and participant observations to explore how security varies depending on social and demographic characteristics and explores the perspectives of affected consumers in the retail environment. The findings will contribute to policy and practice development, providing actionable insights to reduce shoplifting, while also decreasing the need for harsh and punitive approaches to theft reduction. In addition, it will explore some broader social factors that contribute to the phenomenon and ways to address such issues
Cost-Effective Automated UHI Mapping with AI: A Case Study of a Scalable Framework for Climate Equity in San José, California
Get PDFUrban areas experience the Urban Heat Island (UHI) effect, with higher temperatures than rural areas, disproportionately impacting low-income communities. Mapping UHIs is a process that usually requires significant amount of human resources, and is not scalable. The lack of accurate and detailed UHI maps makes it difficult for decision makers to design effective mitigation strategies. In this work we introduce a cost-effective, scalable, and universally applicable UHI mapping framework that leverages open-source data and AI-driven feature extraction from remote sensing imagery. Using various causative factors such as city characteristics, anthropogenic heat, city canyons, and meteorological variables, we create UHI maps for the city of San Jos´e, California. We conducted comprehensive data engineering, including the collection, cleaning, transformation, and integration of spatial and demographic datasets. Our methodology enhances traditional UHI assessment by applying clustering techniques to categorize urban areas by heat intensity, improving map interpretability. Additionally, we trained a supervised machine learning classifier to predict UHI intensity categories for census tracts, enabling scalable categorization of new data. Finally, we conducted an equity analysis to uncover disparities in UHI exposure, highlighting demographic groups disproportionately affected. Our findings show that clustering all UHI causative factors enhances holistic UHI assessment and supports more equitable urban climate resilience planning
Experienced Latinx Urban Gardeners in San Jose, CA, Offer Strategies for Climate Justice and Resilience
Get PDFLow-income and underinvested communities will be disproportionately affected by climate change due to limited resources, inadequate infrastructure, and insufficient support systems. Urban gardeners are responding to the need to adapt to new climate conditions while sustaining their food sources and cultural practices. Many have adapted thanks to local interventions led by the government and non-profit agencies. For this study, I partnered with La Mesa Verde (LMV), a gardening and food justice program that works with low-income Latinx families in San José, and I documented the contributions of experienced Latinx gardeners, especially those with agricultural backgrounds, to climate-resilient gardening in San José. This study uses the Theory of Planned Behavior (TPB) to identify factors influencing the adoption of climate-resilient practices by Latinx urban gardeners. I find that experienced gardeners are more likely to engage in climate-resilient practices than newer gardeners, playing a critical role as community leaders and educators in advancing urban climate resilience. LMV’s model addresses the main components of the TPB. For example, bilingual workshops promote favorable attitudes towards environmental values. Moreover, LMV offers mentoring and cross-training, supported by experienced gardeners. Finally, LMV’s model successfully removes barriers by covering the costs of gardening spaces and materials. LMV’s model provides a replicable strategy for increasing urban climate resilience
Visions of Kleinian Groups
Get PDFDiscrete groups of M¨obius transformations, called Kleinian groups, act on the Riemann sphere. We explore the connection between M¨obius transformations and PSL(2,C), its subgroups, and linear algebraic properties to understand the dynamics of various Kleinian groups, including Fuchsian groups and Schottky groups. In particular, we use Mathematica to program visualizations of Schottky groups and their limit sets
Application of Virtual Reality to Lower Sugar Intake by Altering Sweetness Perception
No full textRegular consumption of excess sugar is linked to multiple nutrition-based diseases. While sugar replacement strategies do exist, they may not be effective substitutes as they fail to mimic taste and cannot be heated in the same manner as sugars. Increasing sweetness perception is an alternative solution for lowering sugar consumption. This experiment tested for alterations in the sweetness perception of sweetened and unsweetened almond milk in different virtual environments. Two music types, the classical song Goldberg Variations, BMV. 998- Variation 13 and a jazz song generated by AI were used. Additionally, fall and spring forest backgrounds were generated by the Blockade Labs 3D image generator. Each participant tasted sweetened and unsweetened almond milk in music only, background only, and combination music and background environments. Results reveal significant differences in sweetness ratings for music type (p=0.015) and between milk types (p\u3c0.001). Viscosity rating differed significantly between backgrounds (p=0.04) and by milk type (p\u3c0.001). Liking ratings varied significantly between backgrounds (p\u3c0.001) and between music (p=0.011). The results suggest that altering music and background may be a strategy to change sweetness and viscosity perception in unsweetened beverages. These results can be used by product developers to help identify factors which influence product acceptability
Spartan Daily, September 10, 2025
Get PDFVolume 165, Issue 8https://scholarworks.sjsu.edu/spartan_daily_2025/1050/thumbnail.jp
