Race/Ethnicity, Juvenile Court Processing and Case Outcomes: Fluctuation or Stability?

• NCJ Number: 246229
• Author(s): Michael J. Leiber, Ph.D.; Jennifer H. Peck, Ph.D.
• Date Published: March 2014
• Length: 113 pages
• Grant Number(s): 2012-IJ-CX-0051
• Agencies: NIJ-Sponsored
• Publication Type: Report (Study/Research); Report (Grant Sponsored)
• Award: Race, Juvenile Court Processing and Case Outcomes: Fluctuation or Stability?

Annotation

In testing Sampson and Laub's structural theory of inequality (community characteristics where youth live influence outcomes in their juvenile justice processing), this study examined whether the socioeconomic characteristics of communities where youth live explains disparity in justice processing of White, Black, and Hispanic youth.

Abstract

The study found minimal to modest support for the structural theory of inequality. Macro-level variables were sometimes found to determine features of social control at each of the four time frames and to a greater extent in explaining case outcomes in the 67 counties in a northeast State; however, these effects were sporadic and not always in the direction predicted by the structural theory of inequality. Poverty and inequality related to race/ethnicity were most often not statistically significant determinants of social control. There was also limited evidence for anticipated relationships between community characteristics and the processing of minorities and drug offenders. In fact, when community characteristics significantly impacted the in the justice system, the effects, at times, resulted in leniency rather than more severe social control. An examination of the results across 30 years generally showed stability in the relationships observed rather than fluctuation or change. Data for this study were provided by the National Juvenile Court Archive (NJCA), representing county-level aggregated information for 16 States that involved 172 counties for just over 30 years (1985, 1995, 2005, and 2009). Ordinary Least Squares regression was used to predict the proportion of referrals petitioned, detained, receiving out-of-home placement, and change models, so as to determine how changes in the independent variables over time influenced changes in the dependent variables over time. A second NJCA dataset represented individual-level data of all delinquent referrals in 67 counties in a northeast State for January 2000 through December 2010. 12 tables, 1 appendix, and approximately 100 references