Conditional race disparities in criminal sentencing: a test of the liberation hypothesis from a non-guidelines state

Objectives: To test the liberation hypothesis in a judicial context unconstrained by sentencing guidelines.

Methods: We examined cross-sectional sentencing data (n = 17,671) using a hurdle count model, which combines a binary (logistic regression) model to predict zero counts and a zero-truncated negative binomial model to predict positive counts. We also conducted a series of Monte Carlo simulations to demonstrate that the hurdle count model provides unbiased estimates of our sentencing data and outperforms alternative approaches.

Results: For the liberation hypothesis, results of the interaction terms for race x offense severity and race x criminal history varied by decision type. For the in/out decision, criminal history moderated the effects of race: among offenders with less extensive criminal histories blacks were more likely to be incarcerated; among offenders with higher criminal histories this race effect disappeared. The race x offense severity interaction was not significant for the in/out decision. For the sentence length decision, offense severity moderated the effects of race: among offenders convicted of less serious crimes blacks received longer sentences than whites; among offenders convicted of crimes falling in the most serious offense categories the race effect became non-significant for Felony D offenses and transitioned to a relative reduction for blacks for the most serious Felony A, B, and C categories. The race x criminal history interaction was not significant for the length decision.

Conclusions: There is some support for the liberation hypothesis in this test from a non-guidelines jurisdiction. The findings suggest, however, that the decision to incarcerate and the sentence length decision may employ different processes in which the interactions between race and seriousness measures vary.