A longitudinal examination of the influence of sex and race on sentencing outcomes in Florida’s rural and urban counties

Understanding the multifaceted factors considered during sentencing is a complex process. An emerging body of literature evaluates whether the level of urbanization has impacts on sentencing outcomes across the United States. Separately, scholars studying the dynamics of sentencing have focused on the consequences of an offender’s race and sex. Studies find that Black and Latinx offenders, especially young males, are more likely to receive harsher sentences compared to their white counterparts. However, relatively little is known regarding whether identified sentencing disparities based on race and sex emerge across types of counties (i.e., rural vs. urban) and whether such patterns have changed over time. Understanding the multifaceted factors that influence sentencing are important for at least three reasons. First, this type of research helps to inform recent sentencing reforms aimed at targeting inequalities within the criminal processing system. Second, prominent criminological theories suggest county-by-county variation in sentencing disparities by demographic characteristics, yet research is only beginning to examine this possibility. Third, examining longitudinal trends in sentencing constitutes a vital step in better understanding the factors that influence judicial decision making. This thesis builds on prior research by asking two specific research questions (1) do individuals from urban counties receive harsher sentences than individuals from rural counties? and (2) does an offender’s race, sex, and county of residence influence sentencing severity? Trends over time will be examined as well. Toward this goal, this thesis will utilize data from the state of Florida that contain all felony conviction sentencing events that occurred between 1994 and 2011 (N = 1,945,816). These data contain information on individual demographic characteristics, prior criminal history, and detailed information regarding the current offense. Also included in the data are the counties in which the sentencing occurred. Logistic regression will be utilized to answer these research questions. Findings from this study will have implications for theory, research, and policy.