Search results for: homelessness

Authors: Stephen D. Fanale

Abstract:

Criminalization creates sizable barriers to housing and perpetuates the cycle of homelessness. Not only does criminalization leave people on the streets and in shelters indefinitely, it also unnecessarily costs the taxpayers. Homelessness is a growing issue throughout the world and criminalizing these human beings is a violation of basic human rights. While ending the criminalization of homelessness may seem like an insurmountable obstacle, there is something that can be done while fighting that battle. While they are under researched as a whole, specialty courts, specifically homeless courts, are a growing vessel that can address some of the barriers associated with criminalization. They divert individuals away from jail while connecting them to services that will help their situation instead of hindering it. The model being used in Salt Lake City, while similar to others throughout the United States, stands alone in its outreach efforts, and should be paving the way for the rest of the world. The following will look at criminalization and different ways of addressing it, and, finally, Salt Lake City’s current operations, including the unique outreach court: Kayak Court.

Keywords: Barriers to housing, criminalization, cycle of homelessness, homeless court, diversion, Kayak Court.

Authors: Lindsay Fink, Sarha Smith-Moyo, Leanne W. Charlesworth

Abstract:

In recent years, the number of individuals experiencing homelessness has increased in the United States. This paper analyzes 2019 data from 16 different emergency shelters in Monroe County, located in Upstate New York. The data were collected through the County’s Homeless Management Information System (HMIS), and individuals were de-identified and de-duplicated for analysis. The purpose of this study is to explore the basic characteristics of the homeless population in Monroe County, and the dynamics of shelter use. The results of this study showed gender as a significant factor when analyzing the relationship between demographic variables and recorded reasons for shelter entry. Results also indicated that age and ethnicity did not significantly influence odds of re-entering a shelter, but did significantly influence reasons for shelter entry. Overall, the most common recorded cause of shelter entry in 2019 in the examined county was eviction by primary tenant. Recommendations to better address recurrent shelter entry and potential chronic homelessness include more consideration for the diversity existing within the homeless population, and the dynamics leading to shelter stays, including enhanced funding and training for shelter staff, as well as expanded access to permanent supportive housing programs.

Keywords: Chronic homelessness, homeless shelter stays, permanent supportive housing, shelter population dynamics.

Authors: Praniil Nagaraj

Abstract:

This paper proposes a method to collect homelessness data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. This paper's contributions can be categorized into three main areas. Firstly, a method for collecting homelessness data is presented, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, are anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data are addressed through simple classification methods, and historical data are utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining these new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data are collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homelessness information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: Crowdsourcing, homelessness, socio-economic policies, statistical analysis.

Authors: Smita S. D. Goorah, Dilish Jokhoo

Abstract:

A personal estimate of a health risk may not correspond to a scientific assessment of the health risk. Hence, there is a need to investigate perceived health risks in the public. In this study, a young, educated and healthy group of people from a tertiary institute were questioned about their health concerns. Ethics clearance was obtained and data was collected by means of a questionnaire. 362 students participated in the study. Tobacco use, heavy alcohol drinking, illicit drugs, unsafe sex and potential carcinogens were perceived to be the five greatest threats to health in this cohort. On the other hand natural health products, unemployment, unmet contraceptive needs, family violence and homelessness were felt to be the least perceived health risks. Nutrition-related health risks as well as health risks due to physical inactivity and obesity were not perceived as major health threats. Such a study of health perceptions may guide health promotion campaigns.

Keywords: Health promotion, perceptions of health risks, university students.