In the United States, housing is treated as a luxury rather than a fundamental human right, as evidenced by the 653,104 people identified as unhoused during HUD’s one-day survey in January 2023. While shelters and housing support programs exist, they cannot solve the problem of chronic homelessness nationwide. The pending Supreme Court decision on Grants Pass v. Johnson could exacerbate the marginalization of this population, potentially displacing unhoused individuals from their communities and subjecting them to increased criminalization. Previous research examines various aspects of homelessness, but despite this information, very little progress has been made toward a housing-for-all program. This study will attempt to gauge the prevalence of automatic rejection for housing based on arbitrary factors like credit score, criminal history, and evictions. It explores the potential correlation between eliminating barriers to initial housing access and creating long-term, stable housing options, particularly when supplemented with wrap-around services. The study will focus on interviewing key stakeholders, including property managers and local politicians, to gauge their perspectives on application rejection rates and their willingness to collaborate with external housing-focused organizations. The data gathered will inform advocacy efforts to promote individual-centered support and establish community partnerships dedicated to advancing housing rights. By shedding light on these critical issues, this research aims to contribute empirical evidence for shaping policy and fostering community-based solutions to address homelessness effectively across diverse communities.

Housing insecurity has been endemic to the university student populations all over the country and efforts are being put into place to assist students in these situations. Despite these efforts, many students experiencing housing insecurity are not getting access to the resources for various reasons. Stigma and other generalized bad ideas about the unhoused community keep students from asking for help when they need it. I will research the effects of stigma on housing-insecure students' choice to access resources or ask for help.

Despite the establishment of the Trafficking Victims Protection Act (TVPA) in 2000, the state and prevalence of human trafficking in the United States has greatly increased. While there exists more information and legislation, it still remains an under-researched and under-evaluated issue. This study looks through the enacted human trafficking federal legislation over the last decade to track whether migrant vulnerability to human trafficking has been further addressed with the evolution of the issue within the country. To provide a relevant analysis, this study will look through human trafficking legislation through the years of 2013-2023 and will focus on the main research question of whether or not migrant vulnerability to human trafficking has been explicitly addressed in federal legislation and, if so, how. It is predicted that due to the issue’s massive increase in awareness throughout law enforcement, policy making, and society as a whole, a majority of human trafficking-focused enacted legislation will explicitly recognize and address migrant victims’ protections against human trafficking within the United States. Keywords: Human Trafficking, Human Trafficking Policy, Migrant, Vulnerability, TVPA

This research explores the problem of racial bias within artificial intelligence (AI) systems, especially within the United States juvenile justice systems. Critical Race Theory (CRT), developed by scholar Derrick Bell, examines the systemic nature of racial biases perpetuated through AI technologies (The Tenets of Critical Race Theory Are Essential for Addressing Population Health Disparities - Lantz, n.d.). Utilizing CRT as the foundational theoretical framework, the study explores how AI tools, such as facial recognition and risk assessment algorithms, exacerbate existing racial disparities. Several key instances of AI-induced bias, including the disproportionate misidentification of African Americans by facial recognition systems and higher error rates in voice recognition for Black Americans, lead to wrongful arrests and unfair sentencing due to a facial recognition mismatch (Buolamwini and Gebru, 2018). In addition, predictive policing algorithms reinforce the cycle of overpolicing and mistrust by targeting minority neighborhoods disproportionately based on historical data reflecting systemic inequalities (Frampton et al., 2022). Furthermore, systematic bias influences decisions about bail, sentencing, and the perceived effectiveness of rehabilitation programs, affecting minority groups disproportionately. This research utilizes a public dataset released by the Charlotte-Mecklenburg Police Department to demonstrate trends in reports. These trends emphasize the cycle of minorities being overpoliced, then reported, then leading to more overpolicing. By grounding the study in CRT, this research emphasizes the importance of addressing the embedded racial biases in AI systems to prevent the perpetuation of systemic racism within the juvenile justice system and beyond.