Nonprofit Studies Commons^™

Strengthening Communities Through Place-Based University Partnerships, Prajakt Pande, Marc T. Sager, Karen Pierce, Jessica Murillo, Rolonda Washington

Presentations

This multiple case study examines university-community partnerships through Place-Based Community Engagement (PBCE) framework, analyzing two nonprofit organizations participating in Community Connect, a university-led capacity-building initiative. Using thematic analysis, we explore how collaborative partnerships shape place-based relationships between universities and community organizations. Findings reveal complementary organizational strengths. Both cases illuminate shared challenges including transportation barriers, balancing funder requirements with community responsiveness, and achieving sustainable community ownership. Cross-case analysis demonstrates that effective PBCE requires systematic investment in relationship-building infrastructure, flexible evaluation approaches honoring community-defined outcomes, and cross-sector partnerships distributing power and resources. This research contributes to understanding universities' role as anchor institutions, …

Advancing Place-Based University- Community Partnerships At The Garcia West Dallas Stem School, Marc T. Sager

Presentations

No abstract provided.

Csey Data Advocacy: Reducing Harm Through Data - Csey Survivors, Maria Barquin Sommers, Brianna Armstrong

SMU Human Trafficking Data Conference

This presentation will focus on the crucial overlap of time management and protection for survivors during data collection. Time management is an essential part of any successful organization, especially when working with vulnerable populations, such as survivors of human trafficking, and facing tight schedules and budgets. It is time- consuming to read through blocks of narratives to find necessary details on survivors, but more importantly, survivors can be harmed by being forced to relive their trauma during data collection. On the other hand, narratives written by advocates can harm survivors if subpoenaed. Documentation data systems that gather quantitative information and …

Can Machine Learning Prevent Human Trafficking? Using Data And Technology To Tailor Policies And Programs Toward Vulnerable Populations In Your Community, Kristen Hubbell

SMU Human Trafficking Data Conference

This presentation will investigate how to use data and technology to prevent human trafficking in communities, before it starts. It will explore the opportunity to utilize a novel machine learning approach to identify local risk factors to guide collaborative, data-oriented prevention programs. Surprising findings from a case study will be shared that challenge existing assumptions on the key drivers of human trafficking.

Reclaiming Data To Transform Anti-Trafficking Systems, Laura Hackney

SMU Human Trafficking Data Conference

AnnieCannons believes that the people closest to the problem are closest to the solution. Yet in the anti-trafficking movement, data about survivors is often collected without survivors. Co-founder and CEO Laura Hackney will discuss how reclaiming data can transform systems of care accountability, and prevention. She will share lessons learned from the development of ResourceFull, a digital platform led and co- designed with trafficking survivors to safely connect individuals to trustworthy services and track outcomes across fragmented care systems. There are ethical, technical, and human-centered challenges of collecting and of using data in a space where safety and trust are …

Enhancing Animal Shelter Operations With Time Series And Machine Learning, Sakava L. Kiv, Donald L. Anderson, Shivam Negi, Jacquelyn Cheun

SMU Data Science Review

Enhancing animal shelter operations through machine learning involves employing a variety of advanced techniques aimed at increasing efficiency, promoting animal welfare, and optimizing resource allocation. This paper explores predictive analytics for adoption rates using regression models to estimate the likelihood of adoption based on historical data, encompassing variables such as breed, health status, and previous adoption trends. Additionally, classification algorithms are utilized to categorize animals by adoption probability, facilitating better resources and marketing prioritization. Clustering algorithms are employed to group animals according to behavior patterns and/or physical health, enabling tailored medical care and enrichment activities that improve their mental and …

Unified In Christ, David Morris

Doctor of Ministry Projects and Theses

Statement of the Question/Problem

The United Methodist Church is facing a season of incredible struggle. The modern American United Methodist Church is facing a crisis of Division during this season of disaffiliation and restructuring. Division within church is not a new phenomenon. In fact, it is not new in the Methodist tradition. This repeating cycle of denominational fracture begs the question, “why does division in the church happen, and how can we avoid it in the future?” Currently the United Methodist Church is dividing supposedly over the issue of human sexuality. I would argue these divisions do not solely rely …

The West Dallas Stem School, Karen Pierce, Kristi Flanders, Rolonda Washington

Presentations

No abstract provided.

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …