arXiv subjects

Maria Y. Rodriguez

Publications and source records attributed to Maria Y. Rodriguez.

4 recordsLinked to original sources

arXiv2025

Open Source Software and Data for Human Service Development: A Case Study on Predicting Housing Instability

Open-source data and tools are lauded as essential for replicable and usable social science, though little is known about their use in resource constrained human service provision. This paper examines the challenges and opportunities of open-source tools and data in human service development by using both to forecast failure to pay eviction filings in Bronx County, NY. We use zip code level data from the Housing Data Coalition, the American Community Survey 5-year estimates, and DeepMaps Model of the Labor Force to forecast rates through July 2021. We employ multilevel (MLM) and exponential smoothing (ETS) models using the R project for Statistical Computing, an oft used open-source statistical software. We compare our results to what happened during the same period, to illustrate the efficacy of the open-source tools and techniques employed. We argue open-source data and software may facilitate rapid analysis of public data - a much-needed ability in human service intervention development under increasingly constrained resources - but find public data are limited by the information they reliably capture, limiting their utility by a non-trivial margin of error. The manuscript concludes by considering lessons for human service organizations with limited analytical resources and a vested interest in low-resourced communities.

cs.CY↗

arXiv2025

Operationalizing Justice: Towards the Development of a Principle Based Design Framework for Human Services AI

Scholars investigating ethical AI, especially in high stakes settings like child welfare, have arguably been seeking ways to embed notions of justice into the design of these critical technologies. These efforts often operationalize justice at the upper and lower bounds of its continuum, defining it in terms of progressiveness or reform. Before characterizing the type of justice an AI tool should have baked in, we argue for a systematic discovery of how justice is executed by the recipient system: a method the Value Sensitive Design (VSD) framework terms Value Source analysis. The present work asks: how is justice operationalized within current child welfare administrative policy and what does it teach us about how to develop AI? We conduct a mixed-methods analysis of child welfare policy in the state of New York and find a range of functional definitions of justice (which we term principles). These principles reflect more nuanced understandings of justice across a spectrum of contexts: from established concepts like fairness and equity to less common foci like the proprietary rights of parents and children. Our work contributes to a deeper understanding of the interplay between AI and policy, highlighting the importance of operationalized values in adjudicating our development of ethical design requirements for high stakes decision settings.

cs.CY↗

arXiv2021

Promises and Pitfalls of a New Early Warning System for Gentrification in Buffalo, NY

Gentrification and its resultant displacement are one of the many "wicked problems" of social policy. The study of gentrification and displacement spans half a century, concerns a variety of spatial, temporal, and social contexts, and describes socio-political processes of across the globe and throughout history. One current iteration of this field of inquiry are efforts to identify "early indicators" of gentrification and/or displacement, or the creation of "early warning systems" (EWS). The current work adds to scholarship on the utility of developing an EWS by examining the methodological considerations required for such systems to serve a justice-oriented preventative role.

cs.SI↗

arXiv2020

Welcome to Gab Alt Right Discourses

Social media has become an important venue for diverse groups to share information, discuss political issues, and organize social movements. Recent scholarship has shown that the social media ecosystem can affect political thinking and expression. Individuals and groups across the political spectrum have engaged in the use of these platforms extensively, even creating their own forums with varying approaches to content moderation in pursuit of freer standards of speech. The Gab social media platform arose in this context. Gab is a social media platform for the so-called alt right, and much of the popular press has opined about the thematic content of discourses on Gab and platforms like it, but little research has examined the content itself. Using a publicly available dataset of all Gab posts from August 2016 until July 2019, the current paper explores a five percent random sample of this dataset to explore thematic content on the platform. We run multiple structural topic models, using standard procedures to arrive at an optimal k number of topics. The final model specifies 85 topics for 403,469 documents. We include as prevalence variables whether the source account has been flagged as a bot and the number of followers for the source account. Results suggest the most nodal topics in the dataset pertain to the authenticity of the Holocaust, the meaning of red pill, and the journalistic merit of mainstream media. We conclude by discussing the implications of our findings for work in ethical content moderation, online community development, political polarization, and avenues for future research.

cs.SI↗