Experiences of LGBTQ Youth Experiencing Homelessness: Implementation of The McKinney-Vento Homeless Assistance Act

The hearts and minds among U.S. legislators need to change about homelessness. While homelessness is certainly a big current issue that many Americans feel that needs to be addressed by our elected leaders, in reality, there are still many debates in Congress about who should be included to receive such funding. Among them, there is bipartisan support in the U.S. Congress for homeless veterans. However, when it comes to LGBTQ youth experiencing homelessness, the bills are introduced by the most progressive left and is quickly defeated. A large body of existing literature exist about LGBTQ youth experiencing homelessness. However, few research literatures address the intersection of McKinney-Vento and LGBTQ Youth Experiencing Homelessness. This study fills the gap of LGBTQ youth experiencing homelessness in relation to the McKinney-Vento Act, the only federal legislation specifically designed to assist K-12 students who are homeless, by looking into their experiences and description of McKinney-Vento. This research is critical for tackling LGBTQ youth homelessness in Los Angeles, which can serve as a blueprint for looking at LGBTQ youth across the United States, as well as looking at gaps in LGBTQ Education Policy at the federal level because it looks at the strengths and failures of McKinney-Vento by the LGBTQ homeless target audience as well as looking into the services they wished they received under the McKinney-Vento Act. At the local level, McKinney-Vento liaisons need clarity on what their day-to-day roles are besides just having toothbrush and toothpaste in a drawer.Twenty-one individual participants in Los Angeles from two different homeless youth shelters participated in an hour-long interview. Participation was completely voluntary. Participants were compensated for their time with a $20 gift card after each interview. About half of the participants identified as cis-gender bisexual or cis-gender gay, and the other half identified as trans non-binary, or bisexual and non-binary. Eight of the twenty-one participants attended schools in California while the rest attended schools throughout the United States. With intersectional minority stress theory and risk amplification theory as the two conceptual frameworks, this was a qualitative exploratory study of young LGBTQ adults who experienced homelessness to better understand LGBTQ youth experiencing homelessness and the services they are or should be receiving under McKinney-Vento. Four findings confirmed the literature and show that not one of the 21 participants were aware of their rights under McKinney-Vento, and all 21 participants experienced difficulties advocating for themselves. First, the findings of higher risk, mental health, and safety among LGBTQ youth experiencing homelessness in my research matches the research from Tierney & Ward (2017). Second, the lived experiences of LGBTQ youth experiencing homelessness attest they felt invisible and ignored by adults at school. Third, there is a gap in literature about LGBTQ youth experiencing homelessness and how K-12 schools are addressing their needs. Fourth, participants reported that schools were using a one-size fits all approach in addressing homelessness among youth. My research goes beyond quantifying levels of higher risk, mental health, and safety; it delves into the daily realities faced by LGBTQ youth grappling with homelessness. By exploring how these individuals perceive and experience risk, as well as understanding 21 unique lived experiences, my study brings forth rich discussions about a vulnerable understudied population, and mitigating the identified risks faced by LGBTQ youth experiencing homelessness

Solutions of Penrose's Equation

The computational use of Killing potentials which satisfy Penrose's equation is discussed. Penrose's equation is presented as a conformal Killing-Yano equation and the class of possible solutions is analyzed. It is shown that solutions exist in spacetimes of Petrov type O, D or N. In the particular case of the Kerr background, it is shown that there can be no Killing potential for the axial Killing vector.Comment: To appear in J. Math. Phy

Issue Debates: Notecards in Extemporaneous Speaking

Editor\u27s Note: We are trying to bring debatable issues in the community to the forefront. Important contemporary issues are discussed at national tournaments, national conventions, and even at the average weekend tournament. But rarely are these issues written about in our journals. To foster those discussions, and in an effort to document some of the history of intercollegiate forensics, we will have an “Issue Debate” in each issue of Speaker & Gavel. For this issue, two well-known and successful coaches (and top-notch extempers in their day) debate the issue of note card use in extemporaneous speaking. We have seen this topic debated at length at multiple national events. But the interaction is limited to less than a minute per speaker and usually involves a dozen different speakers with two dozen different reasons as to why the event description language should or should not be changed. A journal’s format provides an opportunity for two scholars, well-versed in the activity, to express their reasoning on the issues related to this topic. It is an interesting read, and both sides make valid arguments

Explainable AI Helps Bridge the AI Skills Gap: Evidence from a Large Bank

Advances in machine learning have created an “AI skills gap” both across and within firms. As AI becomes embedded in firm processes, it is unknown how this will impact the digital divide between workers with and without AI skills. In this paper we ask whether managers trust AI to predict consequential events, what manager characteristics are associated with increasing trust in AI predictions, and whether explainable AI (XAI) affects users’ trust in AI predictions. Partnering with a large bank, we generated AI predictions for whether a loan will be late in its final disbursement. We embedded these predictions into a dashboard, surveying 685 analysts, managers and other workers before and after viewing the tool to determine what factors affect workers’ trust in AI predictions. We further randomly assigned some managers and analysts to receive an explainable AI treatment that presents Shapely breakdowns explaining why a model classified their loan as delayed and measures of model performance. We find that i) XAI is associated with greater perceived usefulness but less perceived understanding of the machine learning predictions; ii) Certain AI-reluctant groups – in particular senior managers and those with less familiarity with AI – exhibit more reluctant to trust the AI predictions overall; iii) Greater loan complexity is associated with higher degree of trust in the ML predictions; and iv) Some evidence that AI-reluctant groups respond more strongly to XAI. These results suggest that the design of machine learning models will determine who benefits from advances in ML in the workplace