Capstone Projects
MSU Affiliation
Data Science Academic Institute
Advisor
Dr. David May
Abstract
This project investigates the complex relationship between counties that house prisons in the United States and the rurality associated with them. The central research question explores how both county characteristics, such as variables corresponding to cost of living and demographics of a county, and prison characteristics, such as programming available to inmates and staffing levels, differ across the census-designated rural-urban distinctions. Furthermore, the study examines whether modern data science methods can more accurately define and distinguish these characteristics, providing a nuanced understanding of the Prison Industrial Complex (PIC) and its manifestation across various American communities. The motivation for this research is anchored in the ethical imperative to understand the long-term impacts of correctional facilities on their host communities. By examining how counties with similar social, economic, and geographic profiles host prisons, the project seeks to illuminate patterns that might otherwise go unnoticed in the national discourse. Understanding these patterns is crucial for policymakers, reform advocates, and scholars interested in criminal justice, rural and urban studies, and community development. To address these questions, the project employs unsupervised machine learning techniques, specifically clustering algorithms, to analyze a comprehensive dataset encompassing diverse county and prison attributes. The technical implementation leverages open-source Python libraries and employs a range of clustering algorithms to ensure robustness and comprehensive grouping. The results of the clustering analysis provide a new lens through which to view the PIC by offering empirically-derived groupings of counties and prisons.
Publication Date
Summer 7-1-2026
Spatial Coverage
U.S. Corrections Hosting Counties
Temporal Coverage
2019 United States Census Data
Keywords
data science, criminology, sociology, machine learning, artificial intelligence
Disciplines
Criminology | Data Science | Sociology
Recommended Citation
Tuccio, Riley N., "Data-Driven Characterization of Counties in the Prison Industrial Complex using Clustering Analysis" (2026). Capstone Projects. 6.
https://scholarsjunction.msstate.edu/data-capstone/6
