Interactive maps, dashboards, and tables examining how place-based conversion factors — environmental quality, economic opportunity, healthcare access, and social connectedness — predict correctional supervision patterns across Utah's 689 census tracts.
Defense presentation synthesizing the theoretical framework, Simes replication, INLA-BYM2 spatial analysis, and place-based policy framework across all four dissertation chapters. Built with Quarto revealjs.
Research questions and theoretical framework establishing the limits of neoclassical economics in explaining the geography of punishment, and how the capabilities theory repositions community conditions as constitutive of individual possibility.
Replication and extension of Simes' Punishing Places methodology, documenting that 21% of Utah's population lives in tracts bearing 50% of all correctional supervision (Gini = 0.496).
Bayesian spatial modeling identifying which specific conversion factors predict geographic concentration of supervision, with φ = 0.51 confirming collective capabilities matter.
Policy framework translating spatial analysis into a place-based targeting methodology: exceedance probability investment zones, coefficient contribution-based intervention matching, 5 regional cluster profiles, and dual-domain cost-benefit analysis.
This research applies the capabilities approach to understand how place-based "conversion factors" — the environmental, economic, and social conditions of neighborhoods — shape criminal justice outcomes. Using Bayesian spatial modeling (INLA-BYM2) on 49,000+ community supervision episodes across Utah (2016–2023), the analysis reveals that structural neighborhood conditions predict supervision patterns independently of individual characteristics.