Award Information
Description of original award (Fiscal Year 2020, $74,722)
The proposed dissertation is a secondary analysis of federal sentencing guideline data to examine the influence of extralegal factors (race/ethnicity, gender, district) on sentencing outcomes over time. The purpose is to improve upon past guideline research largely based on cross-sectional studies which have consistently detected persistent extralegal effects. The research questions are: 1) how has the influence of race/ethnicity on federal sentencing outcomes changed over time, 2) how has the influence of gender on federal sentencing outcomes changed over time, and 3) how has between-district variation in federal sentencing outcomes changed over time? Sentencing guideline data collected by the U.S. Sentencing Commission are publicly available for a nearly 20-year period (1998 to 2016). The student will collect and merge data at both the case and district level, and examine incarceration and sentence length outcomes. Since the Sentencing Reform Act of 1984 created federal sentencing guidelines, several U.S. Supreme Court decisions (i.e. Koon v. United States, United States v. Booker) and legislation have impacted federal sentencing. There have also been broad shifts in caseloads and demographic characteristics of the U.S. communities. The sentencing guideline data will be supplemented by district-level Federal Judicial Caseload Statistics data and United States Census Bureau data. Multilevel modeling will consider: 1) case, 2) district, and 3) time to assess how federal sentencing outcomes vary on those variables. Cross-level interaction analysis will assess whether extra-legal variable effects have changed over time. Statistical models will apply different interval/ratio level dependent variable techniques (Poisson regression, negative binomial regression). Dissemination includes three academic journal submissions and presentations at national conferences.
Note: This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF
Similar Awards
- Harnessing Artificial Intelligence to Evaluate Microscopic Characteristics of Skeletal Trauma
- Collaborative Strategies in Safeguarding Children: A Community-Centric Approach to Overdose Response
- Multi-level, Mixed Methods Evaluation of Elm City COMPASS: A Comprehensive Approach to 911 Crisis Response