Chapter 1 · Theoretical Framework

Research Questions

Three research questions guiding the dissertation — from spatial description to explanation to policy application.

The spatial capabilities framework developed in this dissertation generates three primary research questions. Together they form a progression from description (how supervision is distributed) to explanation (what place-based factors predict that distribution) to application (how spatial methods can guide policy intervention). Each question is addressed across multiple chapters, with the theoretical architecture developed in the Conceptual Model providing the conceptual foundation for empirical investigation.

1

How is the correctional supervision population spatially distributed across Utah communities?

This question examines the geographic distribution of correctional supervision and its spatial clustering patterns, testing whether correctional supervision concentrates in specific census tracts, whether this concentration exhibits clustering within neighborhoods, and how these patterns relate to one another. Spatial capabilities theory predicts that neighboring communities will have similar supervision rates because they share similar conditions — the same environmental quality, the same job markets, the same services. In other words, what happens in one community should be closely tied to what happens next door.

Spatial Clustering Concentration Curves Regional Variation Urban vs. Non-Metro
Addressed in Chapter 2 →
2

What is the spatial relationship between community corrections and capability deprivations (place-based deficits)?

This question examines how place-based conversion factors — environmental quality, healthcare access, economic opportunity, transportation accessibility, and social connectedness — predict the geographic concentration of correctional supervision, and which domains most strongly constrain the capabilities for successful community participation. The analysis distinguishes between environmental, social, and economic conversion factors to identify which domains most powerfully shape outcomes.

Conversion Factors INLA-BYM2 17 Predictors Spatial Spillovers
Addressed in Chapter 3 →
3

How can spatial Bayesian methods inform place-based policy interventions?

This question bridges the theory of this dissertation to policy application by estimating tract-level coefficient contributions and exceedance probabilities to identify priority areas for place-based intervention and the specific conversion-factor deficits that interventions should address. The analysis provides the evidence base for context-specific intervention strategies, cost-benefit evaluation, and spatial targeting of resources toward capability enhancement.

Exceedance Probabilities Coefficient Contributions Cost-Benefit Regional Targeting
Addressed in Chapter 4 →