Fayetteville, North Carolina, USA. Available online: 04 Aug 2011

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1 This article was downloaded by: [Fayetteville State University] On: 09 August 2011, At: 13:15 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: Registered office: Mortimer House, Mortimer Street, London W1T 3JH, UK Journal of Ethnicity in Criminal Justice Publication details, including instructions for authors and subscription information: Racial Disparities in Juvenile Court Outcomes: A Test of the Liberation Hypothesis Lori Guevara a, Lorenzo M. Boyd a, Angela P. Taylor a & Robert A. Brown a a Department of Criminal Justice, Fayetteville State University, Fayetteville, North Carolina, USA Available online: 04 Aug 2011 To cite this article: Lori Guevara, Lorenzo M. Boyd, Angela P. Taylor & Robert A. Brown (2011): Racial Disparities in Juvenile Court Outcomes: A Test of the Liberation Hypothesis, Journal of Ethnicity in Criminal Justice, 9:3, To link to this article: PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan, sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

2 Journal of Ethnicity in Criminal Justice, 9: , 2011 Copyright Taylor & Francis Group, LLC ISSN: print / online DOI: / Racial Disparities in Juvenile Court Outcomes: A Test of the Liberation Hypothesis LORI GUEVARA, LORENZO M. BOYD, ANGELA P. TAYLOR, and ROBERT A. BROWN Department of Criminal Justice, Fayetteville State University, Fayetteville, North Carolina, USA After decades of research, the exact impact of race on juvenile court outcomes is still a complex matter. The focus of this study is to address the liberation hypothesis as a potential explanation for racial disparities in juvenile court outcomes. This perspective has not previously been applied to juvenile court outcomes. Results from the analyses demonstrate the differential effect of legal and extralegal factors on serious and less serious cases. The results of this study indicate that legal factors such as crime seriousness or prior criminal record and extralegal factors such as race have a varying influence on juvenile court outcomes, and this influence varies depending on the outcome examined and the race of the youth. KEYTERMS Liberation hypothesis, juvenile court, racial disparities INTRODUCTION Research exploring racial disparities in juvenile court outcomes is abundant. Findings from previous research, however, are inconsistent. Some studies have revealed direct race effects (Bishop & Frazier, 1996; Bortner, Sunderland, & Winn, 1985; Conley, 1994; Frazier & Bishop, 1995; Thornberry & Christensen, 1984; Wordes & Bynum, 1995; Wordes, Bynum, & Conley, 1994). Other studies have found that the effect of race is indirect (Bishop & Frazier; 1996; Bortner & Reed, 1985; Frazier & Bishop, 1995; Poole & Regoli, 1980). Still other studies have found cumulative race effects across juvenile court outcomes (Bishop & Frazier, 1988, 1996; DeJong & Jackson, 1998; Johnson & Secret, 1990; Leiber, 1994; McCarthy & Smith, 1986). Finally, some Submitted October 2010; resubmitted February 2011; accepted March Address correspondence to Lori Guevara, PhD, Department of Criminal Justice, Fayetteville State University, 1200 Murchison Road, Fayetteville, NC LGuevara@ uncfsu.edu 200

3 Racial Disparities in Juvenile Court Outcomes 201 studies have indicated that contextual effects such as organizational factors influence juvenile court outcomes (Cohen & Klugel, 1978, 1979a, 1979b; Feld, 1991; Sampson & Laub, 1993; Sanborn, 1996). The purpose of the present study is to advance beyond the routine view of racial disparities in juvenile court outcomes by testing a specific hypothesis related to the influence of legal and extralegal factors in court outcomes. This study uses Kalven and Zeisel s (1966) liberation hypothesis to examine the perspective that racial disparities in juvenile court outcomes are restricted to less serious offenses. This hypothesis has been tested in the adult criminal justice system with support for the notion that extralegal factors such as race influence outcomes for less serious offenses. However, this hypothesis has not been tested on juvenile court outcomes. Specifically, this study hypothesizes that in serious cases, the outcome is influenced by the seriousness of the current offense and the juvenile s prior record, whereas in less serious cases, extralegal factors such as race influence the outcome. RESEARCH ON RACIAL DISPARITIES IN JUVENILE COURT OUTCOMES There is considerable support for the conclusion that legal factors have the most influence on juvenile court outcomes (Bailey, 1981; Bishop, 2005; Black & Reiss, 1970; Carter, 1979; Cohen & Klugel, 1978, 1979a, 1979b; Marshall & Thomas, 1983; Thomas & Sieverdes, 1975). Legal factors such as prior criminal history and the seriousness of the current charge have been the best predictor in research that includes demographic and other extralegal variables. In some research, the influence of extralegal factors dissolves after legal factors are controlled (Belknap, 2001; Carter, 1979; Clarke & Koch, 1980; Dannefer & Schutt, 1982; Fenwick, 1982; Kempf-Leonard & Sontheimer, 1995; Phillips & Dinitz, 1982; Teilmann & Landry, 1981). However, other research has revealed that extralegal factors continue to influence juvenile court outcomes even when legal factors are included (Bishop, 2005; Bishop & Frazier, 1996; Bortner et al., 1985; Bray, Sample, & Kempf-Leonard, 2005; Conley, 1994; Frazier & Bishop, 1995; Guevara, Herz, & Spohn, 2006; Guevara, Spohn, & Herz, 2004; Leiber, 1994; Thornberry & Christensen, 1984; Wordes & Bynum, 1995; Wordes et al., 1994). Pope and Feyerherm s (1990) review of 46 studies on juvenile court outcomes emphasized the need to take extralegal factors such as race into consideration. They concluded that there was substantial support for the statement that there are race effects in operation within the juvenile justice system, both direct and direct in nature (p. 335). They also identified four themes that became apparent from their research. First, selection bias was found at all juvenile court outcomes. Second, the way that race influenced outcomes depended on the outcome examined. Third, the influence of race on

4 202 L. Guevara et al. juvenile court outcomes was complicated when other variables were controlled for in the analysis. Fourth, small race effects at early juvenile court outcome accumulated and became more distinct at later outcomes. This cumulative effect of race was evident in studies that examined the manner in which early outcome race effects (detention and petition) influenced later outcomes (disposition; Bishop, 2005; Bishop & Frazier, 1996; Bortner & Reed, 1985; Frazier & Cochran, 1987; McCarthy & Smith, 1986; Poole & Regoli, 1980). After decades of research, the exact impact of race on juvenile court outcomes is still a complex matter. The goal of this paper is to bring more clarity to the topic by examining a new explanation for racial effects. The focus of the current study is to address the liberation hypothesis as a potential explanation for racial disparities in juvenile court outcomes. This perspective has not previously been applied to juvenile court outcomes. By using this explanation, the study will provide elaboration on the findings of previous research examining the influence of legal and extralegal factors on juvenile court outcomes. THEORETICAL PERSPECTIVE The liberation hypothesis was proposed by Kalven and Zeisel (1966) in their study of jury decision making involving sexual assault cases. They suggested that serious crimes with strong evidence may reduce discretion on the part of jurors, whereas less serious crimes with weak evidence may result in jurors exercising more discretion. Specifically, Kalven and Zeisel stated, The closeness of the evidence makes it possible for the jury to respond to sentiment by liberating it from a discipline of the evidence (p. 165). Under such circumstances, the jury sometimes takes a merciful view of the facts (p. 165). In other words, for serious crimes, jurors are less likely to be liberated to follow their own sentiments and are restricted to following the law in making their decision. As a result, dispositions will closely track with the seriousness of the offense, with harsher outcomes occurring for more serious offenses. However, for non-serious crimes, jurors are more likely to be influenced by their personal feelings. Although Kalven and Zeisel wrote of jurors taking a merciful view of the facts, it is also likely that jurors may then use extralegal factors, including racial discrimination, to decide the outcomes. The liberation hypothesis has been tested at different decision-making points in the adult criminal justice system. Reskin and Visher (1986) examined juror recommendations for sexual assault cases and found that jurors used extralegal factors in cases involving weak evidence. Barnett (1985), Baldus, Woodworth, and Pulaski (1985), and Paternoster (1984) found that the victim s race was a significant factor in the imposition of the death penalty in cases in which there were few aggravating factors. Smith and Damphousse (1998) examined sentences imposed on felony defendants and found that the harshest sentences were reserved for those charged with the most

5 Racial Disparities in Juvenile Court Outcomes 203 serious crimes. Spohn and Cederblom (1991) examined the sentences imposed on defendants convicted of felonies and found that the defendant s race had a direct effect on the incarceration decision in less serious cases only. Leiber and Blowers (2003) explored the extent to which racial discrimination was likely to occur in misdemeanor cases involving less serious cases. They found that race influenced misdemeanor decision making both directly and indirectly. The liberation hypothesis has added to the understanding of racial disparities in the adult criminal justice system and can potentially add a crucial dimension to the understanding of how race matters in juvenile court outcomes. Previous research has consistently found that minorities are overrepresented in the juvenile justice system (Bishop, 2005; Hsia, Bridges, & McHale, 2004; Kempf-Leonard, 2007). Overrepresentation means that although minority youth constitute 16% of the general population between the ages of 10 and 17, they compose 39.1% of the youth detained, 35.9% of those handled formally in the juvenile courts, 33% of the youth adjudicated delinquent, 38.3% of the juvenile cases resulting in out-of-home placements, and 44% of the youth transferred to adult courts (Stahl, Finnegan, & Kang, 2007). An analysis of federal and state efforts to address disproportionate minority confinement found that in 2001 minority youth were overrepresented in every state reviewed and at all decision points (Leiber, 2002). Despite abundant research, there is no clear consensus as to the explanation for the racial disparity in juvenile court outcomes. Therefore, this study uses the liberation hypothesis to examine racial disparity in juvenile court outcomes. The following hypotheses are tested: Hypothesis 1: For serious cases, juvenile court outcomes will be influenced by legal factors such as offense seriousness and priors. Hypothesis 2: For less serious cases, juvenile court outcomes will be influenced by extralegal factors such as race. DATA AND METHODS The data for this study were collected from case files from two juvenile courts as part of a study to examine disproportionate minority contact. The two counties used in this study were the two largest counties in a midwestern state. The first county (urban) included a large metropolitan area with a total population of 416,444, with minorities representing 16% of this population (U.S. Census Bureau, 1990). Approximately 23% of the urban county s total population was between the ages of 7 and 17. Moreover, 69% of the juvenile population was White, 15% was African American, 15% was Latino, and 1% was Native American or Asian American. The second county (suburban) was the second largest county in the state and included a moderately

6 204 L. Guevara et al. sized metropolitan area. This county had a total population of 203,013, with minorities representing 5% of this total (U.S. Census Bureau, 1990). Approximately 25% of the total population was juveniles younger than age 19. Of this juvenile population, 92% was White, 3% was African American, 2% was Latino, 1% was Native American, and 2% was Asian American. Cases were selected from each county using a random sampling procedure. The urban county had 15,728 delinquency referrals. These referrals were stratified by race and gender and then chosen at random, with a resulting sample of 1,500. Referrals that did not have a court file or that were transferred to another jurisdiction were dropped, for a final sample of 1, In the suburban county, there were 6,825 delinquency referrals. Given the small number of minority youths in this county, all referrals involving non-white youth were selected, as were a random sample of 16% of referrals involving White youth. This procedure resulted in an initial sample of 1,181 referrals. Removal of referrals that did not have a court file or that were transferred to another jurisdiction yielded a final sample of 1,047. The sampling procedures used in the two counties resulted in an undersampling of White youth and an oversampling of non-white youth relative to their percentages in the total referral population. As a result, the data and subsequent analyses were weighted to reflect each racial category s representation in the total referral population. 2 Data for each of these cases were derived from archived probation files using standard data collection forms. Because of missing information in these files, many case characteristics (such as school status or the socioeconomic status of the juvenile or the juvenile s family) could not be included in the analysis. The final variables used in this study are presented in Table 1. Dependent Variables Racial disparity in juvenile court outcomes is best examined with a multistage approach. Race effects can be more noticeable at some outcomes than at others, and early outcomes (i.e., pre-detention) can influence later outcomes (i.e., disposition). In addition, minor race effects at early outcomes may accumulate during subsequent outcomes, and a compound race effect may occur. Therefore, this study included the pre-adjudication detention and disposition outcomes as two distinct dependent variables. The pre-adjudication detention outcome was operationalized as pre-detained (coded 1) or not pre-detained (coded 0). Disposition measured the final outcome after the juvenile had been adjudicated delinquent and was captured using three levels of severity: 0 for dismissal of the charges, 1 for probation, and 2 for out-ofhome placement. For the analyses, the final category (placement) was the reference category. 3

7 Racial Disparities in Juvenile Court Outcomes 205 TABLE 1 Definitions of Variables Used Variable Definition Dependent variables Pre-detention Disposition Independent variables White Gender Age Prior record Current offense Felony Misdemeanor County Independent Variables 0 = no 1 = yes 0 = dismissed 1 = probation 2 = placement 0 = no 1 = yes 0 = male 1 = female Interval variable Ratio variable 0 = no 1 = yes 0 = no 1 = yes 0 = suburban 1 = urban The independent variables in the analyses included legal and extralegal characteristics. The legal factors included prior record and offense seriousness. The extralegal factors included race, age, gender, pre-adjudication detention status, and county. Because of the small number of Latinos, Native Americans, and Asian Americans in the sample, these cases were combined with those involving African Americans into a non-white category. 4 Race was therefore coded 1 for White and 0 for non-white. Gender was a dichotomous variable (male = 0, female = 1), age was an interval measure of the youth s age at the time of arrest, and prior record was measured by the youth s number of prior court referrals. Offense seriousness was operationalized as felony or misdemeanor. Pre-adjudication detention (yes = 1, no = 0) was also included as a control variable in the disposition analyses. The final variable included in these analyses was the county in which the case was adjudicated (urban county = 1, suburban county = 0). Analysis Procedures Multivariate analyses using binary and multinomial logistic regression were conducted to determine the predictors of juvenile court outcomes. Because the pre-adjudication detention outcome was dichotomous, binary logistic regression was used. Multinomial logistic regression was used for analysis of

8 206 L. Guevara et al. the three-category disposition variable. 5 This technique estimates the effects of explanatory variables on a dependent variable with unordered response categories (Aldrich & Nelson, 1984; Liao, 1994; Menard, 1995). For this study, the probability of being dismissed or receiving probation was compared to the probability of receiving an out-of-home placement. The focus of this study is the influence of legal factors across race on juvenile court outcomes. In other words, the influence of legal factors may vary by the race of the juvenile, the foundation of the liberation hypothesis. The data were partitioned by race in order to produce separate estimates for White and non-white youth and allow for a comparison of the coefficients for each group (Albonetti, 1987; Myers, 1985). Then the equality of the coefficients across models was tested using the z test (Paternoster, Brame, Mazerolle, & Piquero, 1998). Comparing these estimates for the two outcomes (pre-adjudication detention and disposition) determined whether the effect of legal factors varied by race. RESULTS Descriptive Statistics Table 2 presents descriptive statistics using weighted data for the entire sample. The descriptive statistics indicate that a majority of the youth were White (56%), and a majority were male (83%). In addition, a majority of the youth were charged with a misdemeanor (55%), the mean age was years, and the average number of prior referrals was A majority of the youth were processed in the urban county (69%). Most of the youth were not pre-detained (64%), and a majority of the youth received either probation (46%) or dismissal of charges (40%) at the disposition hearing. There were significant correlations between the independent variables and one or more of the disposition outcomes (see Table 3). However, in most cases the relationships were moderately weak, with a few (noted here) being almost nonexistent. Race influenced all four decisions: White youth were less likely than non-white youth to be pre-detained, to have the charges dismissed, or to receive an out-of-home placement this last association was very small (.093). However, White youth were more likely than non-white youth to receive probation. Gender was significantly related to the predetention and placement decisions only. Girls were less likely than boys to be pre-detained and more likely than boys to receive a placement, although the effect here was pretty small (.025). Youth with priors were more likely to be pre-detained, to have the charges dismissed, and to receive a placement but were less likely to receive probation. Youth charged with a felony were more likely to be pre-detained and to receive probation or placement and were less likely to have the charges dismissed. Finally, jurisdiction also had an effect: Youth processed in the urban county were less likely to receive

9 Racial Disparities in Juvenile Court Outcomes 207 TABLE 2 Descriptive Statistics (N = 8,525) Variable % n TABLE 3 Correlations Race White 56 4,761 Non-White 44 3,764 Gender Male 83 7,093 Female 17 1,432 Age a Younger than , , , , Priors b , , More than Current offense Felony 45 3,851 Misdemeanor 55 4,674 County Urban 69 5,926 Suburban 31 2,599 Pre-detained No 64 5,440 Yes 36 3,085 Disposition Dismissed 40 3,367 Probation 46 3,929 Placement 14 1,229 a Mean = b Mean = Dependent Variable Independent Variable Pre-Detained Dismissed Probation Placement White Female Age Priors Felony Urban county Pre-detained p.05.

10 208 L. Guevara et al. probation, although they were more likely to be pre-detained, to have the charges dismissed, and to receive an out-of-home placement (.036 a pretty small effect). Pre-Adjudication Detention Outcome The results of the logistic regression analyses (see Table 4) indicate that both legal and extralegal variables influenced the pre-adjudication detention outcome in the full model. The legal variables (priors and felony) were significant in that youth charged with a felony (b = 1.989) and those with priors (b = 0.264) were more likely to be pre-detained. The extralegal variables (race, gender, age, and county) were also significant. Specifically, White youth (b = 0.376) and girls (b = 0.215) were less likely to be pre-detained, whereas older youth (b = 0.138) and those processed in the urban county (b = 2.090) were more likely to be pre-detained. Legal variables (priors and felony) were also significant in the two race-disaggregated models (see Table 5). Specifically, White youth charged with a felony or with priors were more likely to be pre-detained than White youth charged with a misdemeanor or without priors. This finding was also true for non-white youth in that non-white youth charged with a felony and those with priors were more likely to be pre-detained than non-white youth charged with a misdemeanor or without priors. Therefore, legal variables had a significant influence on the preadjudication detention outcome, and it was significant for both White and non-white youth. The results of the z test (see Table 5) reinforce the finding that the effect of legal variables did not vary across race. In other words, regardless of race, youth charged with a felony and who had priors were more likely than those charged with a misdemeanor or without priors to be TABLE 4 Logistic Regression Results for Pre-Adjudication Detention Outcome for the Full Model (N = 3,085) Overall Variable Pre-Detained B SE White Felony Female Age Priors Urban county Intercept Pseudo R log likelihood 2, p.05.

11 Racial Disparities in Juvenile Court Outcomes 209 TABLE 5 Logistic Regression Results for Pre-Adjudication Detention Outcome Partitioned by Race White Youth Non-White Youth (n = 1,199) (n = 1,886) Pre-Detained Odds Pre-Detained Odds Variable B SE Ratio B SE Ratio z Felony Female Age Priors Urban county Intercept Pseudo R log likelihood , p.05. pre-detained. These results fail to support the hypothesis that for less serious cases, juvenile court outcomes will be influenced by extralegal factors such as race. However, they do support the hypothesis that for serious cases, juvenile court outcomes will be influenced by legal factors such as offense seriousness and priors. Disposition Outcome The results of the multinomial logistic regression analyses of the disposition outcome are presented in Tables 6 (full model) and 7 (race-disaggregated models). In the full model, the extralegal variable of race did not influence the disposition outcome. However, other extralegal variables (gender, age, county, and pre-detention status) did influence the disposition outcome. Specifically, girls and youth who were pre-detained were less likely to have TABLE 6 Multinomial Logit Results for Disposition Outcome for the Full Model (N = 8,525) Dismissed a Probation a Variable B SE B SE White Felony Female Age Priors Urban county Pre-detained Intercept Pseudo R log likelihood 7, a Estimated with placement as the reference category. p.05.

12 210 L. Guevara et al. the charges dismissed or receive probation and so were more likely to receive an out-of-home placement. Older youth were more likely to have the charges dismissed or receive probation and thus less likely to receive an out-ofhome placement. Youth processed in the urban county were more likely to have the charges dismissed than to receive an out-of-home placement. For the full model, legal variables (priors and felony) varied in their influence on the disposition outcome. Youth charged with a felony were less likely to have the charges dismissed and more likely to receive an out-of-home placement. However, offense seriousness did not influence the probation outcome. Finally, youth with prior offenses were less likely to have the charges dismissed or receive probation and were more likely to receive an out-of-home placement. In the model including only White youth, the legal variables (priors and felony) influenced the disposition outcome. Having a felony reduced the odds of having charges dismissed (odds ratio [OR] =.283) or receiving probation (OR =.703) compared to getting an out-of-home placement (the reference category). The findings were similar for those youth with priors: OR =.701 (charges dismissed) and OR =.699 (receive probation). In the model including only non-white youth, the legal variables (priors and felony) had a differential effect on the disposition outcome. Similar to White youth, non-white youth charged with a felony or with priors had reduced odds of having the charges dismissed (ORs =.788 and.820, respectively) compared to receiving an out-of-home placement. However, in contrast to White youth, non-white youth did not face increased odds of receiving probation compared to out-of-home placement (OR =.912, ns). Non-White youth did face reduced odds (OR =.633) of receiving probation if they had prior offenses. Therefore, legal variables had an influence on the disposition outcome, but the significance varied. The results of the z test (see Table 7) provide support for the differential effect of these legal variables across race on the disposition outcome. The effect of offense seriousness was significant across race for dismissal of charges in that youth charged with a felony were less likely than youth charged with a misdemeanor to have the charges dismissed, an effect more pronounced for White youth (OR =.283). In addition, the effect of priors was also significant across race for the dismissal of charges. Specifically, youth charged with a felony were less likely than youth charged with a misdemeanor to have the charges dismissed, and this also impacted White youth more than non-white youth (ORs =.707 and.820, respectively). These results also indicate that there was no differential effect of legal variables (priors and felony) on the probation outcome across race. Both White and non-white youth with priors or charged with a felony were less likely to receive probation and were more likely to receive an out-of-home placement. These results only partially support the research hypotheses. The influence of legal factors (priors and felony) was only significant across race for

13 Racial Disparities in Juvenile Court Outcomes 211 TABLE 7 Multinomial Logit Results for Disposition Outcome Partitioned by Race White Youth Non-White Youth (n = 4,761) (n = 3,764) Variable B SE Odds Ratio B SE Odds Ratio z Dismissed a Felony Female Age Priors Urban county Pre-detained Intercept Probation a Felony Female Age Priors Urban county Pre-detained Intercept Pseudo R log likelihood 4, , a Estimated with placement as the reference category. p.05. one disposition outcome: the dismissal of charges. For serious cases, juvenile court outcomes were influenced by legal factors such as offense seriousness and priors. However, for serious cases, the outcomes were also influenced by extralegal factors (such as race), but not in the expected direction. For example, these legal factors had a differential effect across race on the dismissal of charges, with the effect more evident for White youth. For less serious cases, juvenile court outcomes were influenced by extralegal factors (such as race), but again only for dismissal of charges. Specifically, non-white youth charged with a misdemeanor were more likely than White youth charged with a misdemeanor to have the charges dismissed. DISCUSSION AND CONCLUSION The purpose of this study was to use the liberation hypothesis to examine racial disparity in juvenile court outcomes. This study tested the hypotheses that for serious cases, juvenile court outcomes would be influenced by legal factors such as offense seriousness and priors, and that for less serious cases, juvenile court outcomes would be influenced by extralegal factors such as race. The findings from this study partially support the liberation hypothesis. Results from the multivariate analyses demonstrate the differential effect of legal and extralegal factors on serious and less serious cases, the foundation

14 212 L. Guevara et al. of the liberation hypothesis. For example, this study found that race influenced all of the following decisions: White youth were less likely than non-white youth to be pre-detained, to have the charges dismissed, or to receive an out-of-home placement. Moreover, this study found that White youth were more likely than non-white youth to receive probation. It can also be noted that jurisdiction also had an effect: Youth processed in the urban county (which had a larger minority population) were less likely to receive probation, although they were more likely to be pre-detained and to have the charges dismissed. However, the nature of the effect depends on the outcome examined. For the pre-adjudication detention outcome, the results do not support the hypothesis that for less serious cases, juvenile court outcomes will be influenced by extralegal factors such as race. The results do support the hypothesis that for serious cases, juvenile court outcomes will be influenced by legal factors such as offense seriousness and priors. For the disposition outcome, legal factors such as priors and offense seriousness had a varying influence across race on the dismissal of charges although not on the probation outcome. In addition, the direction of the influence was unexpected, with White youth charged with a felony or priors more likely than non-white youth to receive an out-of-home-placement than dismissal of charges. The results of this study support the notion that extralegal factors such as race influence juvenile court outcomes. The possible explanation for these findings is a path for future research. In exploring the varied effect of extralegal factors such as gender and age on outcomes for serious offenses, two perspectives that complement the liberation hypothesis may be useful: the focal concerns approach and attributional theory. These two perspectives propose that decision makers are influenced by their own sentiments and individual judgments. According to the focal concerns approach, three focal concerns influence decision makers: the youth s blameworthiness and the degree of harm caused the victim; protection of the community; and practical implications of sentencing decisions (Steffensmeier, Ulmer, & Kramer, 1998, p. 766). The first concern is related to the seriousness of the offense and other legally relevant factors. The second concern reflects judges assessments of the youth s dangerousness and recidivism potential. The third concern is related to assessment of the broader impact of the punishment given. These assessments focus on impacts on the offender as well as on the court itself. Because judges rarely have enough information to accurately determine dangerousness, recidivism potential, or punishment impact, they develop a perceptual shorthand (p. 776) based on stereotypes that can be linked to characteristics such as race, gender, and age. Applying a focal concerns approach to examining juvenile court outcomes may help to further clarify the role of race and other extra legal factors in judicial decision making. Attributional theory proposes that decision makers are influenced by their individual judgments of the reasons behind a given youth s delinquent

15 Racial Disparities in Juvenile Court Outcomes 213 behavior (Bridges & Steen, 1998). Specifically, delinquency is attributed either to the youth s environment (e.g., living in a crime-prone area) or to his disposition (e.g., sociopathy). Dispositional attributions increase perceived offender culpability, which then leads to more severe punishment. Perhaps the differential use of race, gender, and other extralegal factors in juvenile case processing may reflect variations in the use of disposition-based attributions for juvenile crime. To apply either a focal concerns approach or attributional theory to explaining juvenile court outcomes, more research is needed on the individual perceptions of judges and other individuals in the court system. This will allow researchers to examine whether and how such perceptions are affected by the legal and extralegal factors of case and whether they vary at each stage of the juvenile court process. This research would benefit from the collection of qualitative data gathered from interviews with juvenile court officials, among others. Finally, this study substantiates the notion that the use of a multistage approach to understanding juvenile court outcomes is the preferred approach to examining the role of legal and extralegal factors in these outcomes. As past research has found, effects are different at different stages of the juvenile journey. The current results reinforce this view by showing differing effects of legal and extralegal factors at different stages. A multistage approach allows for a thorough examination of the influence of legal and extralegal factors on various juvenile court outcomes and should be the direction of future research. Research testing the liberation hypothesis in juvenile court outcomes would also benefit from a justice by geography approach. Jurisdictional disparities in juvenile court outcomes have existed since the enactment of the Juvenile Court Act in According to Feld s (1991) research, such disparities may be linked to differences in the philosophical orientation of juvenile courts (i.e., traditional vs. due process). This type of examination may provide a refined picture of the role of discretion in juvenile court outcomes. In summary, the results of the current study indicate that legal factors such as the serious of a crime or prior criminal history and extralegal factors such as race have a varying influence on juvenile court outcomes and that this influence varies depending on the outcome examined and the race of the youth. Although the results do not point to a simple conclusion concerning the influence of legal and extralegal factors, they do add to the understanding of how issues of race matter in juvenile court outcomes. NOTES 1. The dropped referrals reflect cases that were dropped or transferred to another jurisdiction early in the process. Therefore, a comparison of the dropped and included referrals was not possible.

16 214 L. Guevara et al. 2. In the urban county, White male referrals were given a weight of 20, White female referrals a weight of 12.50, African American male referrals a weight of 14.29, African American female referrals a weight of 7.14, and Native American and Asian American referrals a weight of 4. In the suburban county, no-action White referrals were given a weight of 20, no-action non-white referrals a weight of 3.60, petitioned White referrals a weight of 7.69, and petitioned non-white referrals a weight of For the two juvenile courts in this study, dismissal of charges was an option at the disposition hearing after the youth had been adjudicated a delinquent. Therefore, this category was included in the dependent variable. 4. T tests were conducted to determine whether there was a statistically significant difference between outcomes for African American, Latino, and Native American youth. Results indicated no significant differences, so these racial categories were combined into a non-white category. 5. Ordered logit was attempted, but because the analysis failed the score test, this type of analysis could not be used. REFERENCES Albonetti, C. (1987). Prosecutorial discretion: The effects of uncertainty. Law & Society Review, 21, Aldrich, J., & Nelson, F. (1984). Linear probability, logit and tobit models. Thousand Oaks, CA: Sage. Bailey, W. (1981). Preadjudicatory detention in a large metropolitan juvenile court. Law and Human Behavior, 5, Baldus, D., Woodworth, G., & Pulaski, C. (1985). Monitoring and evaluations contemporary death sentencing systems: Lessons from Georgia. U.C. Davis Law Review, 18, Barnett, A. (1985). Some distribution patterns for the Georgia death sentence. U.C. Davis Law Review, 18, Belknap, J. (2001). The invisible woman: Gender, crime and justice. Belmont, CA: Wadsworth. Bishop, D. (2005). The role of race and ethnicity in juvenile justice processing. In D. F. Hawkins & K. Kempf-Leonard (Eds.), Our children, their children: Confronting racial and ethnic differences in American juvenile justice (pp ). Chicago, IL: University of Chicago Press. Bishop, D., & Frazier, C. (1988). The influence of race in juvenile justice processing. Journal of Research in Crime and Delinquency, 25, Bishop, D., & Frazier, C. (1996). Race effects in juvenile justice decision-making: Findings of a statewide analysis. Journal of Criminal Law and Criminology, 86, Black, D., & Reiss, A., Jr. (1970). Police control of juveniles. American Sociological Review, 35, Bortner, M., & Reed, W. (1985). The pre-eminence of process: An example of refocused justice research. Social Science Quarterly, 66, Bortner, M., Sunderland, M., & Winn, R. (1985). Race and the impact of juvenile deinstitutionalization. Crime & Delinquency, 31, Bray, T., Sample, L., & Kempf-Leonard, K. (2005). Justice by geography: Racial disparity and juvenile courts. In D. Hawkins & K. Kempf-Leonard (Eds.), Our children, their children: Confronting racial and ethnic differences in American juvenile justice (pp ). Chicago, IL: University of Chicago Press.

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