Incident and Individual Characteristics Predicting Rule Violations in Jail

• In Event: Violence and Misconduct in Carceral Institutions: Patterns, Risks, and Institutional Response

Abstract

Jails rely on internal disciplinary procedures to sanction unwanted behaviors (“misconduct”) that jeopardize safety and security interests. Prior literature on institutional misconduct largely relies on prison-based samples to identify risk factors for violence or serious misconduct, as well as disparate sanctions associated with rule violations. However, a growing body of scholarship identifies a correctional management practice employed by correctional staff to prioritize institutional response by dismissing minor rule violations: selective rule enforcement. To advance understanding of the reported rule violations, this study used demographic and administrative records of rule violations in a large metropolitan jail to identify key classes of rule violators and predictors of reported rule violations. We first analyzed disposition of misconduct cases using multilevel logistic regression models to identify statistically significant predictors of guilty misconduct at the rule violation incident (Level 1) and unique person-stay (Level 2). In addition to the multilevel logistic models, we conducted exploratory latent class analysis to identify classes (e.g., typologies) of rule violators in the jail. Findings will aid jail administrators in expanding evidence-based classification processes at intake. This study is the first in a three-study dissertation examining the jail enforcement decision-making process.

Authors

• Hayley Jean Carlisle, George Mason University

• Evan Marie Lowder, George Mason University

• David B. Wilson, George Mason University