Abstract
This study investigates disparity as it exists in the conviction of Latino, African American, and White offenders in Chicago homicide cases. The study participants were adults who had been identified by the Chicago Police Department as suspects in homicide incidents for the years 1990 through 1995. Information about the offender, victim, homicide incident, and adjudication of the homicide case in court was collected from police and court records. Logistic regression modeling was used to determine the odds of conviction for Latino, African American, and White homicide offenders at the adjudication decision point of criminal case processing. Results indicated that in Chicago homicide cases, when deciding guilt or no guilt for Class M Felony murder, neither race nor ethnicity mattered; what did matter the most was the offender–victim relationship, the number of charges filed against the offender, and the mode of conviction. This study continues the important tradition in racial and ethnic disparity studies of measuring the effect of offender–victim dyads on case outcomes. It builds on prior research in 2 ways: (a) by measuring the impact of the offender–victim dyad's race and ethnicity on conviction odds and (b) by expanding the scope of case-processing research through examining decision making at the pre-sentence adjudication stage, a point researchers have heretofore rarely examined.
Notes
1. The court information from homicide cases for the study participants was stored on hard-copy paper documents. The process of locating the court cases of homicide offenders, printing hard copies of these records, and then automating the information from the hard copies for analysis proved to be expensive and cumbersome. To expedite the data collection process and facilitate a cost-effective research project, samples were selected of homicide offenders from the two largest racial/ethnic populations (Latino offenders/Latino victims and Black offenders/Black victims).
2. The calculation for the Black-on-Black sample was n = .50(1–.50)÷[(.05÷1.96)2 + .50(1–.50)÷1,131]. The calculation for the Latino-on-Latino sample was n = .50(1–.50)÷[(.05÷1.96)2 + .50(1–.50)÷234].
3. For this study, a technique of weighting referred to as “grossing-up weights” was used. Weights or a number were assigned to members in each subsample that replicated the numbers in that sample to their numbers in their population so that the sample accounted for the total population. See Babbie (1995, p. 221) for an example of this type of weighting.