2017/10/06 by Rachael Weiss Riley, Riley, Rachael Weiss, Jacob Kang-Brown +10
Health Professions · Social Sciences · #Computers and Society (cs.CY) #Crime Patterns and Interventions #Criminal Justice and Corrections Analysis #FOS: Computer and information sciences #Homelessness and Social Issues
paper · pdf · doi:10.48550/arxiv.1710.02453
openalex publication_date 2017/10/06 · openalex created_date 2022/08/30 · openalex updated_date 2026/07/28
As the rate of incarceration in the United States continues to grow, a large\nbody of research has been primarily focused on understanding the determinants\nand drivers of federal and state prison growth. However, local jail systems,\nwith 11 million admissions each year, have generated less research attention\neven though they have a far broader impact on communities. Preliminary time\ntrend analysis conducted by the Vera Institute of Justice (Vera) uncovered\ndisparities in county jail incarceration rates by geography. Contrary to\nassumptions that incarceration is an urban phenomenon, Vera discovered that\nduring the past few decades, pretrial jail rates have declined in many urban\nareas whereas rates have grown or remained flat in rural counties. In an effort\nto uncover the factors contributing to continued jail growth in rural areas,\nVera joined forces with Two Sigma's Data Clinic, a volunteer-based program that\nleverages employees' data science expertise. Using county jail data from 2000 -\n2013 and county-specific demographic, political, socioeconomic, jail and prison\npopulation variables, a generalized estimating equations (GEE) model was\nspecified to account for correlations within counties over time. The results\nrevealed that county-level poverty, police expenditures, and spillover effects\nfrom other county and state authorities are all significant predictors of local\njail rates. In addition, geographic investigation of model residuals revealed\nclusters of counties where observed rates were much higher (and much lower)\nthan expected conditioned upon county variables.\n