A multilevel assessment of sentencing disparity in Kansas: do sentencing disparities differ by individuals and judicial districts?

Abstract

Government researchers, policymakers, and sentencing scholars have placed special emphasis on evaluating the sentencing schemes used in courts around the nation. Most past studies focused on extralegal characteristics of the defendant. The current study is different in that emphasis is also placed on the potential influence of judges and judicial districts. Focusing attention on sentencing judges permits the ability to link characteristics of arguably the most important courtroom actor to sentencing outcomes. Assessing judicial districts incorporates another distinct contribution to the study of courts: an examination of whether social context affects sentencing decisions. A common focus of past literature rests on assessing the direct impact of extralegal factors such as race/ethnicity, gender, and socioeconomic status on sentencing variation. Less research has been devoted to how elements such as sociodemographic, economic, and political characteristics of courts and their jurisdictions affect sentencing outcomes. The present study highlights the importance of considering these factors when examining sentencing disparities and establishes why Kansas is the ideal setting for such study. Data examined in this study derive from the Kansas Sentencing Commission, the U.S. Census Bureau, Kansas Office of Judicial Administration, and the Kansas Secretary of State’s Office. These datasets were utilized to conduct a multilevel analysis of sentencing disparity in Kansas. The levels assessed include at the individual case- and judicial district-levels. Hierarchical linear modeling (HLM) techniques were used to control for the complexity of this multilevel approach. Key contributions of this study include: (1) providing an in-depth analysis of inter-judge sentencing disparity, (2) conducting a multilevel sentencing study in a Midwestern state, (3) inclusion of Hispanics in the analysis and (4) use of up-to-date data on a timely topic.