A Multilevel Test of the Racial Threat Hypothesis in One State’s Juvenile Court

Abstract

Noting the paucity of research on the racial threat hypothesis in the juvenile courts, this study examined the interplay of defendant characteristics and country-level characteristics on dispositions. Data were retrieved from the Department of Juvenile Justice files in South Carolina and were analyzed using multinomial logistic hierarchical linear modeling. Results revealed support for the racial threat hypothesis, as racial inequity operated in a different manner (more punitively) for Black defendants. Larger Black populations in counties also led to an increased use of punitive sanctions. In addition, concentrated disadvantage effects were found, and heightened levels of teenage population led to higher incarceration rates for Black defendants. Limitations of this study, implications for stakeholders/practitioners, and directions for future research are discussed.

Keywords

minorities juvenile delinquency juvenile justice theory

Introduction

Concerns about disparities in sentencing have been pervasive in the criminological literature, and evidence of these disparate sentences persists despite the efforts from lawmakers to reduce them, including the introduction of structured sentencing guidelines (Johnson, 2005, 2006; Spohn & Holleran, 2000; Steffensmeier, Ulmer, & Kramer, 1998; Ulmer & Johnson, 2004). Underlying the disparate outcomes in sentencing, perhaps, is the perceived fear that particular offenders who possess dangerous characteristics need to be removed from mainstream society (Leiber & Johnson, 2008). These concerns are perhaps even more difficult to reconcile for juvenile offenders who at various times have been described as vicious and remorseless (DiIulio, 1995; Feld, 1990, 1991; Fox, 1996). DiIulio (1995) in particular warned of the coming juvenile superpredator, which some argued paved the way for a more criminalized juvenile court (Feld, 2003).

In recasting juvenile offenders as predators, an important racial dimension was grafted onto the debate about what to do about juvenile offending and, more broadly, the juvenile court as a whole (Feld, 1999). A number of scholarly works and commentary identified instances where young, urban males (Black and Latino) were described not only as threatening but also as belonging to dangerous classes (Rothenberg & Heinz, 1998; Sampson & Laub, 1993; M. Welch, Price, & Yankey, 2004). Even more, their criminality reflected ongoing social disorganization, decay, and moral poverty that were entrenched in their communities.

Some argue that these attitudes toward minority juveniles have not significantly changed, nor have the approaches taken to address their criminality, especially as it relates to punitive and deserts-based punishments where fairness has seemingly been replaced by concerns about safety (Bush, 2010; Feld, 1999; Podkopacz & Feld, 2001; Zimring, 1998). In light of this fact, some scholars have proposed using the racial threat perspective as an organizing framework for understanding how racial, economic, and political forces may shape criminal justice policies and other forms of social control (Eitle, D’Alessio, & Stolzenberg, 2002; Jacobs & Helms, 1999; Liska, 1997). In using this perspective, a number of studies have examined sentence disparities among adult habitual offenders (Crawford, Chiricos, & Kleck, 1998), federal sentencing guidelines (Feldmeyer & Ulmer, 2011), sentencing and incarceration decision making (Wang & Mears, 2010a, 2010b), and support for strict sentencing policies (Johnson, Stewart, Pickett, & Gertz, 2011; King & Wheelock, 2007).

Notwithstanding this body of research, there is still some uncertainty regarding the extent to which the racial threat perspective is applicable to the juvenile court (cf. Johnson, 2008; Leiber, Peck, & Rodriguez, 2016; Thomas, Moak, & Walker, 2013). While there is a plethora of research outside of the scope of the racial threat perspective which has found that urban, minority youth are more likely to receive more punitive sentences compared with their suburban White counterparts (D’Alessio & Stolzenberg, 1993; DeJong & Jackson, 1998; Leiber, 1995; MacDonald, 2003), there still remains a large gap in our knowledge with regard to how race shapes juvenile court decision making, and whether it exerts pressure on the juvenile courts to affirm the best interests of offenders, or whether it pushes them to be more punitive and community safety oriented (i.e., confinement vs. probation).

Moreover, we do not know the extent to which political influences such as an increased minority presence of juvenile court judges (more Black judges and women) tempers or exacerbates threat perceptions for various juvenile offenders. Finally, there remains uncertainty with regard to whether context matters: How does racial threat manifest itself at the individual level (case level) and the county level (Armstrong & Rodriguez, 2005; Leiber et al., 2016)? Several scholars have discussed the importance of using multilevel modeling to disentangle the effects of racial threat, but such scholarship is sparse in the juvenile justice literature (Freiburger & Jordan, 2011; Leiber et al., 2016; Rodriguez, 2013; Thomas et al., 2013).

The present study seeks to shed light on juvenile sentencing outcomes through the theoretical lens of the racial threat hypothesis. In particular, this study uses the three dimensions of Blalock’s thesis—political threat, economic threat, racial threat—to examine whether minority defendants (Black juveniles) are disadvantaged in the disposition decisions (social control) of juvenile court judges. Using data collected from the South Carolina Department of Juvenile Justice (DJJ), we examine whether the differences that we see in juvenile court disposition can be explained from the racial threat perspective or whether there may be other extralegal factors at play that are yet unaccounted for in the juvenile courts.

Theoretical Perspective

Racial Threat Hypothesis

Scholars who study sentencing have noted that race affects outcomes for adult offenders across a number of criminal justice contexts (Crawford et al., 1998; Crow & Johnson, 2008; Jacobs & Carmichael, 2001; Steffensmeier et al., 1998). Nonetheless, there are still questions about the degree to which race affects sanctioning for juvenile offenders and whether there are decision points occurring prior to the dispositional stage where race effects are most likely to be observed (Morrow, Dario, & Rodriguez, 2015; Peck, Leiber, & Brubaker, 2014). A number of theoretical perspectives have been offered that purport to explain the observed differences among these offenders (Bishop & Frazier, 1996; Fagan, 1996; Kurlychek & Johnson, 2004; Leiber & Johnson, 2008). Yet, scholars have not fully explored the utility of the racial threat perspective and its critical insights with regard to the behaviors of criminal justice actors. Blalock (1967) argued that a racial hegemony exists which is maintained by a dominant group. This racial hegemony not only reinforces prejudice and interracial hostilities, but it also frames and interprets perceived threats to the status quo by outsider or subordinate groups.

One manifestation of these perceived threats can be seen in the analysis of voting strength, voting patterns, and even policies aimed at reducing or diluting voting strength (Avery & Fine, 2012; Behrens, Uggen, & Manza, 2003). Because the dominant groups have no real desire to relinquish or share their power or alter the status quo, and also because they embrace “political exclusiveness” (Behrens et al., 2003), they use their position and resources to dilute the strength of perceived outsiders and other subordinate groups (Blalock, 1967; Bobo & Hutchings, 1996; Turk, 1969). What is much less discussed in the literature, however, is what other forms are these political threats likely to take beyond traditional elective offices, for example, judgeships. It is indeed possible that the growth in the number of minority judgeships held by women and minorities would temper some of the harsher aspects of social control embraced by the dominant political group as growth in minority populations increased success in judicial appointments. This observation forms one of the central ideas of this study.

In addition, the racial threat perspective posits that there is a relationship between increases in the size of minority populations and changes in the methods of social control that are used to maintain the political, social, and economic hegemony of the dominate group¹ (Blalock, 1967; Horowitz, 1985; Stolzenberg, D’Alessio, & Eitle, 2004). One manifestation of this increased social control is heightened punitiveness in sentencing that is presumably used to squelch dissent as well as social and political unrest (Novak & Chamlin, 2012; Stolzenberg et al., 2004). This punitiveness also manifests itself in a myriad of other forms, including the disproportionate arrests of minorities (Eitle et al., 2002), unequal incarceration policies and practices (Jacobs & Carmichael, 2001), police mobilization (Earl, Soule, & McCarthy, 2003; Liska, Lawrence, & Benson, 1981), police use of excessive/deadly force (Parker, MacDonald, Jennings, & Alpert, 2005), felon disenfranchisement (Behrens et al., 2003), and the expansion of punitive policies aimed at poor, largely minority youth (Jacobs & Helms, 1999; K. Welch & Payne, 2010a, 2010b; Wilson, 1997).

What emerges from this research is the idea that there is a discernible racial dimension to the criminal justice policies both locally and nationally. However, the manner in which race operates may not be fully understood, in that it may manifest itself through proxies such as the size of the potential crime committing population (teenagers in the population) or fear of victimization (violent crime rate). Thus, we argue that the racial iconography of the past is now recast in terms of criminal justice policies and practices designed to allay concerns about crime.

Structural and economic changes may also create competition between a minority group and the dominant group. Importantly, these structural and economic changes may assume myriad forms, including changes in housing sectors, “white flight” and resegregation, labor market instability, and “job sprawl” (DeFina & Hannon, 2013). These labor dislocations and other macrolevel changes may serve as a medium for the increased perception of a minority group threat toward the majority group’s continued economic viability (Eitle et al., 2002). Consequently, increased punitive attitudes toward minority groups, as well as calls for increased criminal justice penalties, may be a by-product of insecurity about future economic uncertainty (King & Wheelock, 2007). Thus, we can expect that components of the racial threat hypothesis will be played out on a landscape characterized by, among other things, changes in the composition of urban areas and changes in the “non-native” population.

Race and the Juvenile Court

Concerns about the impact of race on the juvenile justice system are well documented in the empirical literature.² There are some indications that minority youths are greatly overrepresented in arrests, referrals to juvenile court, detention, and confinement notwithstanding the overall declines seen in both violent and property crimes (Bishop & Frazier, 1996; DeJong & Jackson, 1998; Leiber, 1995; Rodriguez, 2013; Sampson & Laub, 1993). Although methodologies and theoretical explanations vary (see Engen, Steen, & Bridges, 2002), the empirical literature suggests that both legally relevant and extralegal factors (particularly race) may magnify the influence of race on juvenile court dispositions (Carmichael, 2010; Desai, Falzer, Chapman, & Borum, 2012; Guevara, Herz, & Spohn, 2006; Steffensmeier et al., 1998; Ulmer & Kramer, 1998).

Also, a number of empirical studies have discussed the importance of accounting contextual factors as they relate to race, juvenile justice, and juvenile court decision making (Armstrong & Rodriguez, 2005; Britt, 2000; Rodriguez, 2007; Sampson, 1986). Whereas some studies have shown that there is a relationship between neighborhood, urbanism, and juvenile delinquency (Peeples & Loeber, 1994), there are equally compelling arguments that this relationship is highly complex and perhaps attenuated by a number of other contextual factors (Sampson, Morenoff, & Gannon-Rowley, 2002). Regardless, the evidence seems to support the belief that neighborhood mechanisms such as poverty and concentrated disadvantage become synonymous with risk and dangerousness, and result in much more negative juvenile court outcomes for Black juveniles compared with their White counterparts (Rodriguez, 2013).

Interestingly, there are some empirical studies that neither find support for the racial threat hypothesis (Hayes-Smith & Hayes-Smith, 2009) nor racial/ethnic bias in juvenile court outcomes (Cohen & Klugel, 1978). Notwithstanding, this research seems to demonstrate that context matters insofar as processes within the juvenile courts that mitigate some of the harsher aspects of juvenile adjudications. For example, Kupchik and Harvey (2007) found little evidence for racial bias; however, there was some evidence that contextual factors, such as highly trained defense attorneys, shielded many minority offenders from the vagaries of illusory “therapeutic care” (pp. 431-432). Similarly, Cohen and Klugel (1978) found that while rampant bias does not permeate the juvenile court, there may nevertheless be some “seepage” that precedes juveniles’ initial entry into the court process itself which could likely account for the disparate outcomes for racial minorities. If these observations are correct, then scholars should try to uncover how and the extent to which these “pre-entry” juvenile court processes disadvantage minority juveniles. In the end, there are divergent views on whether race and ethnicity play a part in juvenile adjudications. The present research is an attempt to ferret out whether race plays a role in increased social control (harsher juvenile court dispositions) as evinced by the greater use of secure detention for Black offenders when compared with their White counterparts.

The Juvenile Court, Juveniles, and the Racial Threat Hypothesis

Admittedly, the historical/traditional role of the juvenile court was focused on the “best interests of the child.” It is clear from Julian Mack’s (1909) commentary that there were myriad concerns with the lack of distinctions between adults and juveniles in the courts. His views on the failings of the justice system with regard to juveniles are best summarized as follows:

. . . instead of the state’s training its bad boys so as to make of them decent citizens, it permitted them to become the outlaws and outcasts of society; it criminalized them by the very methods that it used in dealing with them . . . [I]t did not ask how he had come to do the particular act which had brought him before the court. It put but one question, “Has he committed this crime?” It did not inquire, “What is the best thing to do for this lad?”

This rather strong indictment of the state was a driving impetus for the creation of the juvenile court. This view also carried considerable weight until the “get tough” movement began to pick up steam in the 1980s and its supporters pushed back against the perceived failures and leniency of the juvenile court. Significant among the “failures” was that the juvenile court was not tough enough on juveniles who were committing serious and violent crimes (Feld, 2003; Podkopacz & Feld, 1996). Supporters of the “get tough” movement also argued that there was a new “breed” of juvenile that the juvenile and criminal justice system needed to deal with in a much more forceful manner (DiIulio, 1995; Fox, 1996). Importantly, there were some scholars who argued that many of the “get tough” measures that were adopted during this period had a decidedly racial component (Feld, 1999, 2003; Ward, 2012). As we argue in this research, the shift from “best interests” to blameworthiness, culpability, and punishment fueled many of the tougher social control policies that were adopted at the state level. Accordingly, we believe that the racial threat hypothesis not only provides us with a unique opportunity to examine just how entrenched these punitive policies are in the juvenile justice system, but may also provide a window into the racialized nature of social control that overlay many of these policies.

Notwithstanding the growing body of empirical research examining the economic, political, and social dynamics of racial threat as it relates to adult offenders, there is comparatively less research with regard to how these contexts may operate for juvenile offenders (Andersen, 2015; Bishop, Leiber, & Johnson, 2010; Carmichael, 2010; Freiburger & Jordan, 2011; Leiber & Fox, 2005; Leiber & Johnson, 2008; Leiber & Mack, 2003). For example, the research on detention decisions has produced inconsistent findings with regard to perceived racial threat. On one hand, Blalock’s assumptions with regard to race and population composition find support to the extent that there is an increased likelihood for negative outcomes when the racial/ethnic composition of counties increases (Armstrong & Rodriguez, 2005). On the other hand, there is also research which has found that perceived racial/ethnic threat may only be indirectly, minimally, or not at all related to the detention decision (Rodriguez, 2007; Thomas et al., 2013).

In other areas of juvenile research, support for the racial threat hypothesis has been equivocal. Freiburger and Jordan (2011), for example, found that Black youths were significantly disadvantaged in the juvenile court. That is, the decision to formally petition the juvenile court increased when poverty rates within communities increased, thereby disproportionately affecting Black youths due to higher levels of Black poverty within the state. On the other end of the spectrum, Leiber et al. (2016) failed to find support for racial threat at three different stages of the juvenile court process—initial processing, adjudication, and disposition. Still, we know very little about how racial threat affects dispositional decisions for serious and violent juvenile offenders. Moreover, we have even less knowledge regarding how political and economic threats may shape decision making for these offenders (Carmichael, 2010, 2011; Carmichael & Burgos, 2012). Few researchers have attempted to disentangle how sentencing outcomes are affected by perceived racial, economic, and political threats.³ Thus, a meaningful discussion about the applicability of Blalock’s theory to juvenile courts cannot begin until we gain a better understanding of how the various dimensions of perceived threats may manifest, broadly speaking, in criminal justice decision making and also more concretely as discrete outcomes, such as secure confinement and probation.

The current study seeks to empirically test the three distinct dimensions of Blalock’s thesis—political threat, economic threat, and racial threat—as measured by the violent crime rate. We examine whether each respective dimension of threat exerts an influence on sanctions (secure confinement, probation, or alternative sanctions) for juvenile offenders.⁴ Given the paucity of research focusing on juvenile offenders and sanction outcomes (cf. Freiburger & Jordan, 2011; Rodriguez, 2007), the present study provides some insights into how race, economics, and other political considerations may influence the decision to impose sanctions on juvenile offenders who are perceived as dangerous. Furthermore, it is posited that minority youth, especially poor minority youth, may be more likely to be perceived as threats and consequently, they are more likely to receive more severe disposition (secure confinement) when compared with their White counterparts (Leiber & Johnson, 2008), especially those minority youths coming from disadvantaged communities (Thomas, Moak, & Walker, 2013).

Assumptions and Hypotheses

There are a range of dispositions available to juvenile court judges in South Carolina, including probation, community service/mentorship, restitution, and commitment to state or private facilities (§63-19-1410). Serious and violent juvenile offenders are also subject to juvenile court jurisdiction in light of (SC§63-19-1440 (D) (E)). Drawing upon Blalock’s racial threat perspective, several hypotheses will be formulated. The first research hypothesis is grounded in the perception that minority youth are more threatening than their White counterparts. Specifically, this hypothesis is premised on the idea that minority (Black) youths are more dangerous, belligerent, angry, and violent (DiIulio, 1995; Fox, 1996; Payne & Welch, 2010) necessitating their removal, even if temporary, from the community. As noted by Payne and Welch (2010), quoting Duncan (2000), there is an “urban pedagogy” that informs how those in power view Black youth. Such pedagogies operate at a number of institutional levels from the schools to the criminal justice system. Within the criminal justice system, we can perhaps see the most pernicious effects of these views about Black youths.

Hypothesis 1 (H1): Minority (Black) youths will be sentenced to secure confinement at higher rates than their White counterparts.

Blalock’s (1967) thesis, in part, argues that there is a relationship between perceived threat and the racial composition of a community. Specifically, Blalock predicted that there would be a “non-linear relationship (with increasing slopes) between minority percentage and the intensity with which certain types of beliefs are held” (p. 166). While many of the beliefs about minority youth (Black youth) are exaggerated, Blalock notes that they serve to justify harsh and often extreme forms of punishment. As such, we expect perceptions of dangerousness to increase as the minority (Black) population increases. Concomitantly, we should see more minority (Black) youths sentenced to secure confinement as the Black population increases in size. However, where there are already high levels of discrimination and the minority (Black) population has reached some maximum size or level, we should expect negligible increases in the use of punitive sanctions.

Hypothesis 2 (H2): An increase in the relative size of the Black population will increase the use of secure confinement for Black youths.

Blalock (1967) acknowledged that political power/behavior is hard to “isolate and appraise,” especially given its relationship to social control (p. 161). Nevertheless, he believes that the mobilization of political resources to effect change, in some form, is possible notwithstanding a group’s numerical size in the community. Importantly, political mobilization is most likely to occur when there are increasing levels of education and tolerance within communities. Rather than conceptualizing political mobilization in terms of voting patterns/behavior (Eitle et al., 2002; Giles & Hertz, 1994), we employ a measure that takes into account the progress that minority groups (minorities and women) have made in a community toward assuming leadership positions not just in the political arena but also as leaders in the criminal justice system.⁵ Given evidence suggesting judge sex and race may influence sentencing decisions (Van Slyke & Bales, 2013), we should expect to see a tempering in how sanctions are meted out to juvenile offenders. In other words, secure confinement will be used less in those jurisdictions where there is a minority or female bench presence.

In South Carolina, family court judges (juvenile court judges) are elected by members of the state legislature. Minimum qualifications are based on age (32 or older), residency (resident of circuit), and experience (licensed attorney for 8 years). Importantly though, the legislature of this state is very conservative, male, and very “White.” As of 2016, the political composition of the lower house of the legislature was 77 Republican and 46 Democrat (28 R/18 D in the Senate). In light of the fact that the state’s General Assembly elects juvenile court judges, it is possible that the judges who are “elected” would also largely reflect the political and racial makeup of this body. However, we also believe that judges are occasionally “elected” who do not reflect the political, racial, and gender composition of the General Assembly. At present, there are 39 male judges and 29 female judges. Also, the racial breakdown is 58 White judges and 10 Black judges. Our argument is not that an increasing number of juvenile court officials will mitigate culpability and dangerousness. Rather, we argue that as the judicial bench (juvenile court judges) becomes more diverse, it is possible that the “political exclusiveness” that resulted in many of the harsher social control policies will be, to some degree, “softened.”

In addition, this research is cognizant of the fact that a change in the size of the minority population, especially in urban areas, can influence discriminatory behavior. Yet Blalock (1967) noted that researchers should not infer a direct causal relationship between urbanization and discrimination. Rather, he argues that “a change in percent Negro could indirectly affect discrimination levels, not because of the increased numbers per se but because of the peculiar characteristics of the migrants” (p. 176). Thus, it is important for researchers investigating racial threat to be careful of the inferences that they may draw regarding the significance of urban population centers. Nevertheless, we believe that it is important to include a measure that taps into what has been variously described as racial density (Voss, 1996).

Hypothesis 3 (H3): As the representation of racial minorities and women as juvenile court judges increases, there will be an increased use of probation.

Hypothesis 4 (H4): As urban population centers increase in size (percent urban), there will be an increased use of secure confinement.

Blalock (1967) argued that resources span a number of dimensions, including economic (money, property), legal (right to vote, bear arms), and other privileges (educational access). Several researches have acknowledged the importance to examining how the competition for resources, especially economic resources, can alter how social control mechanisms are used within a community (Bontrager, Bales, & Chiricos, 2005; Kirk, 2008; Parker, Stults, & Rice, 2005). Also important, research in this area has suggested that the economic and regulatory capacity of a community may affect confinement decisions (Rodriguez, 2013). Given these findings, we anticipate that perceptions of threat will be heightened where there are high levels of competition for economic resources as measured by concentrated disadvantage. Moreover, we believe that where the economic and regulatory capacity of a community is strained or under severe stress, there will be a greater tendency to use sanctions such as secure confinement.

Hypothesis 5 (H5): Secure confinement will be used more often in communities that are characterized by higher levels of concentrated disadvantage.

Data and Method

Data were retrieved from the DJJ files in South Carolina for the years 2007 to 2012. In this state, juvenile court jurisdiction extends to persons less than 17 years old (§63-19-20). During the years included in this study, approximately 11,440 serious and violent offenses were committed by juvenile offenders statewide (South Carolina DJJ, 2013). The initial population of interest for this study consisted of 1,436 juvenile offenders who were adjudicated delinquent in juvenile court and under DJJ supervision during the study period.⁶ However, this population was further reduced to 1,164 after the removal of 272 offenders who appeared multiple times, using only their most recent referral, and also offenders who were below the age of 14. Furthermore, we excluded all cases where the solicitors dropped the charges, cases that were nol prossed, and cases resolved prior to adjudication. We further note that the sample of offenders used in this research was restricted to juveniles who committed serious and violent offenses as defined by the state statute (§16-1-60);⁷ however, we purposefully excluded juveniles who were waived to adult court (§63-19-1210) and all juveniles charged with status offenses (§63-1-40(6)). Case processing information including offender and offense characteristics, and type of sanction was extracted from the case files. Sensitive information (social security number [SSN], addresses, birth dates, and names) was redacted and not coded to maintain the confidentiality of the offenders.

Dependent Variable

The dependent variable is a measure of the disposition outcome: probation (n = 413), secure confinement (n = 406), and “other” (n = 345). Probation serves as the reference category.⁸ We note that in the Table 2 models, we estimate the log-odds of confinement versus probation and, in the Table 3 models, the log-odds of “other” versus probation. The category “other” was constructed as a means to capture outcomes other than secure confinement and probation (§63-19-350), including house arrest, forestry/marine/wilderness programs, and community supervision. Descriptive statistics are provided in Table 1.

Table 1.

Descriptive Statistics (N = 1,164).

Outcome variable	N	Frequency	Minimum	Maximum
Secure confinement	406	34.9	—	—
Other outcome	345	29.6	—	—
Probation	413	35.5	—	—
Individual level	N	Frequency	Minimum	Maximum
Black	678	58.2	0	1
Male	995	85.5	0	1
No priors	469	40.3	0	1
Chronic offender	672	57.7	0	1
Accomplices	183	15.8	0	1
Referral age 14	347	29.8	0	1
Referral age 15	422	36.2	0	1
Robbery	73	6.3	0	1
Criminal sexual conduct	145	12.5	0	1
Major assault	245	21.1	0	1
Burglary	316	27.2	0	1
Minority bench presence	641	55.1	0	1
Female bench presence	881	76.1	0	1
County level	M	SD	Minimum	Maximum
% Urban	61.289	20.783	0	141.54
Teenage population	0.508	0.500	0	1
% Black population	29.959	1.89	6.8	71
Black population change	−0.830	1.895	−7.6	2.7
White-to-Black income ratio	1.787	0.298	1.342	2.666
Non-native population	1.779	0.942	0.020	5.567
Concentrated disadvantage	0.445	1.000	−1.362	3.585
Violent crime rate	61.289	21.51	21.38	141.54

Individual-Level Variables

Our first set of predictors includes age (ages 14, 15, 16) and offense, where age 16 serves as the reference category. The justification for the use of these age categories is drawn from §63-19-20(1) which defines the jurisdiction of the juvenile court. We include specific offense categories—assault, criminal sexual conduct, robbery, Burglary I, and Burglary II—based on the expectation that the more serious and/or violent the offense is, the less opportunity there will be for judicial discretion (Armstrong & Rodriguez, 2005; Freiburger & Jordan, 2011; Leiber & Mack, 2002; Leiber et al., 2016; Rodriguez, 2013). Dummy codes were created for each offense, with “1” indicating that the offense was the final charge at disposition. In addition, several measures related to the juveniles’ background are included—race (Rodriguez, 2007) was dummy coded “1” for Black (vs. White);⁹ sex (Leiber et al., 2016) was dummy coded “1” for male; prior offense history (no priors) was dummy coded “0” if there were no adjudications for any prior offense and coded “1” for prior adjudication (Ryan, Abrams, & Huang, 2014); age at referral (Kurlychek & Johnson, 2004) was dummy coded “1” and “0” for each respective age grouping; chronic offending (Baglivio, Jackowski, Greenwald, & Howell, 2014; Kempf-Leonard, Tracy, & Howell, 2001) was dummy coded “1” if juvenile had three or more prior juvenile court referrals; and accomplices (Burrow & Lowery, 2015) were dummy coded “1” if the offender had one or more accomplices. These individual-level measures serve as Level 1 predictors in the hierarchical linear modeling (HLM) models.

Racial, Economic, and Political Threat Variables

Several measures of racial threat are examined (all derived from the American Community Survey, 2008-2012).¹⁰ Percent Black is the proportion of Black residents in each county, and it is used to assess the relative size of the Black population (Eitle et al., 2002; Parker, Stults, & Rice, 2005). We included the change in percent Black within counties and the White-to-Black income ratios as representations of the economic threat between counties, races, and the degree to which threat has been contained (Leiber et al., 2016). The percentage of teenagers between the ages 15 and 17 and whether they exceed more than 5% of the population in a county are also included, given the argument that a large teenager population may affect perceptions of perceived threat (Chiricos et al., 2001; Stolzenberg et al., 2004). We also explore the effects of the percentage of non-citizen residents living in a county as a matter of economic threat (Rocha & Espino, 2009; Stewart, Martinez, Baumer, & Gertz, 2015; Wu & D’Angelo, 2014).

The measure of concentrated disadvantage used in this research is grounded in a number of important concepts, including economic instability, low educational attainment, lack of economic opportunities, and low levels of success (Giles & Buckner, 1993; McNulty & Bellair, 2003; Quilllian, 1995). Specifically, our Concentrated Disadvantage scale is derived from the percentage of the county population with less than a ninth-grade education (Rocha & Espino, 2009), the county unemployment rate (Wang & Mears, 2010b), the percentage of households with incomes less than US$10,000 within counties (Eitle et al., 2002), and the number of persons less than 50 (Kubrin & Weitzer, 2003) within a county (four items, Cronbach’s α = .74, eigenvalue = 4.21), suggesting that these items load on a single latent construct (see Wang & Mears, 2010b).

We also include a measure of the violent crime rate per county (Eitle et al., 2002; Stolzenberg et al., 2004). Finally, the percentage of the county population living within an urban area is included as a predictor of racial threat (Wang & Mears, 2010b). It is presumed that in areas with higher proportions of urban populations, especially with higher Black populations, there is an increased likelihood of interracial interaction (Blau, 1977). The nature of these interactions is often sculpted by the economic and social conditions ascribed to the community (Arvanites, 2014; McCall & Parker, 2005). Finally, we included measures for female and minority judges (Songer, Davis, & Haire, 1994; Van Slyke & Bales, 2013) as a means of tapping into the concept of political threat/mobilization.¹¹

Statistical Analysis

Given the hierarchical structure of the data (juveniles nested within counties and counties within circuits), hierarchical linear models is used.¹² hierarchical linear models aids in the estimation of effects within individual units, formulating and testing hypotheses about cross-level effects, and the partitioning of variance and covariance components among levels (Lee & Bryk, 1989; Raudenbush & Bryk, 2002). In our analysis, we estimated multinomial logistic regression models. Prior to analysis, diagnostics for error propagation were also undertaken. First, we checked for multicollinearity among the regressors, noting a variance inflation factor (VIF) value no higher than 2.9 and a tolerance value no lower than .42. Second, to address the issue of heteroskedastic and clustered errors, robust standard errors were estimated to adjust for heteroskedasticity and correlated errors (Arellano, 1987; Kiefer & Vogelsang, 2002). hierarchical linear models 7 only provides a deviance statistic to assess relative model fit but not absolute fit, a limitation of hierarchical linear models 7 (Raudenbush, Bryk, Cheong, Congdon, & du Toit, 2011).

Our hierarchical linear models models were estimated based on the impacts of individual-level characteristics (Level 1) and county-level characteristics (Level 2) on juvenile court outcomes. We note that some scholars have observed that it is important to account and correct for correlated error when pooling defendants from different counties (Britt, 2000; Ulmer & Johnson, 2004). Therefore, we adjusted for the correlated error across defendants processed in the same county and controlled for the cross-county differences for the outcome variable. All Level 1 variables were added as uncentered (Daun-Barnett, 2008). Next, Level 2 (county-level data) measures were introduced to determine the importance of the racial threat variables on juvenile court outcomes. These variables were centered to ease interpretation, with the exception of teenage population (binary variable) and percent urban (meaningful 0 value; Daun-Barnett, 2008; Raudenbush & Sampson, 1999). Finally, we calculated intraclass correlation coefficient (ICC) values to ascertain the between-group variance (Woltman, Feldstain, MacKay, & Rocchi, 2012). In Tables 2 and 3, our final estimated models are presented.

Table 2.

Multilevel Multinomial Logistic Regression Models Predicting the Log-Odds of Secure Confinement Versus Probation (N = 1,164).

	Standard model	Black offender model
	Model I	Model II
Individual level
Black	−0.026 (.142)	—
Male	0.478 (.209)*	0.504 (.216)*
No priors	−0.979 (.199)***	−0.970 (.193)***
Chronic offender	0.843 (.194)	0.898 (.134)*
Accomplices	−0.580 (.230)*	−0.302 (.064)^†
Referral age 14	−0.419 (.203)*	−0.367 (.204)^†
Referral age 15	−0.264 (.186)	−0.313 (.187)
Robbery	0.965 (.331)**	0.858 (.307)**
Criminal sexual conduct	1.618 (.306)***	0.909 (.337)**
Major assault	0.447 (.157)*	−0.182 (.063)*
Burglary	0.520 (.201)*	−0.162 (.059)*
Minority bench presence	−0.795 (.476)^†	−0.626 (.215)
Female bench presence	−0.115 (.132)^†	0.118 (.075)
County level
% Urban	−0.033 (.009)***	0.011 (.003)***
Teenage population	−0.093 (.395)	0.328 (.127)**
% Black population	0.043 (.014)**	−0.015 (.004)***
Black population change	0.227 (.078)**	−0.079 (.027)***
White-to-Black income ratio	0.656 (.583)	−0.229 (.253)^†
Non-native population	0.177 (.212)	−0.061 (.070)
Concentrated disadvantage	−0.529 (.222)***	0.230 (.071)***
Violent crime rate	0.013 (.004)	−0.004 (.002)
Intercept	−1.489*	−2.207***
ICC	.487	.549
F	7.207***	6.119***

Note. Robust standard errors in parentheses. ICC = intraclass correlation coefficient.

†

p < .10. *p < .05. **p < .01. ***p < .001.

Table 3.

Multilevel Multinomial Logistic Regression Models Predicting the Log-Odds of Probation Versus “Other” Sanctions (N = 1,164).

	Standard model	Black offender model
	Model III	Model IV
Individual level
Black	−0.070 (.183)	—
Male	0.500 (.243)*	−0.119 (.168)
No priors	−0.641 (.183)***	0.247 (.218)
Chronic offender	0.517 (.172)**	−0.436 (.149)**
Accomplices	−0.286 (.174)	0.240 (.216)
Referral age 14	−0.442 (.204)*	−0.052 (.232)
Referral age 15	−0.227 (.187)	−0.193 (.204)
Robbery	1.487 (.383)***	0.525 (.517)
Criminal sexual conduct	0.678 (.219)**	−1.085 (.313)***
Major assault	0.634 (.168)***	0.002 (.206)
Burglary	0.376 (.232)***	0.283 (.281)
Minority bench presence	0.376 (.407)	0.688 (.340)*
Female bench presence	−0.568 (.447)	−0.130 (.309)
County level
% Urban	0.010 (.009)	0.010 (.214)
Teenage population	0.483 (.269)^†	1.174 (.323)***
% Black population	−0.016 (.013)	0.191 (.081)*
Black population change	−0.156 (.063)**	−0.053 (.081)
White-to-Black income ratio	−0.374 (.519)	0.264 (.714)^†
Non-native population	−0.191 (.160)	0.118 (.179)
Concentrated disadvantage	0.217 (.184)	0.104 (.218)
Violent crime rate	0.008 (.004)	0.003 (.004)
Intercept	−1.414*	−2.193***
ICC	.476	.551
F	6.245***	5.961***

Note. Robust standard errors in parentheses. ICC = intraclass correlation coefficient.

†

p < .10. *p < .05. **p < .01. ***p < .001.

Findings

Table 2 presents the estimates of the individual- and county-level predictors as well as the models (Models I and II) for the log-odds of secure confinement, whereas Table 3 presents the log-odds of receiving probation versus some “other” disposition (Models III and IV). Two models were estimated per outcome. The standard (main effects) models (Models I and III) focus on the main effects of racial threat with no cross-level interactions. The second (cross-level interaction) models (Models II and IV), given the assumption that race influences the final disposition (Eitle et al., 2002; Leiber et al., 2016; Thomas et al., 2013), present the cross-level interactions with Black defendants and the county-level predictors.

We begin our discussion of the findings with the individual-level predictors. The odds of secure confinement versus probation were 1.61 times (exp [.478]) greater for males than for females (Model I). A similar result can be seen in Model III, where a male’s odds of receiving secure confinement versus probation were 1.64 times greater compared with females (exp [.500]). In Model II, the odds of secure confinement were 1.65 times (exp [.504]) greater for Black males compared with White males; however, there was no significant effect on probation in Model IV. These findings accord with a number of recent studies which have reported that Black offenders tend to receive significantly more severe outcomes than other offenders (Demuth & Steffensmeier, 2004; Rodriguez, 2013; Steffensmeier & Demuth, 2006). With regard to bench characteristics (minority and female judges), we observe that Black judges had a marginal, but significant, effect on the confinement decision as seen in Model I (Spohn, 1990; S. Welch, Combs, & Gruhl, 1988). In Model IV, however, the effect of minority bench presence was considerably stronger where we found that Black offender’s odds of receiving probation were higher. This finding may indicate that bench diversity matters in terms of the severity with which Black and White juvenile offenders are disposed.

Several additional individual-level predictors were significant in both the secure confinement and probation models. As seen in Table 2, the effects for “no priors” and “chronic offender” in Model I were significant. In both the standard and Black offender models (Models I and II), offenders who had no priors were roughly equal in terms of the odds of being sentenced to secure confinement. The effect was somewhat stronger in Model III but there was no significant difference in Model IV. Importantly, the odds of receiving secure confinement for Black offenders who were labeled as chronic offenders¹³ were 2.45 times (exp [.898]) greater (Model II).

There was a similarly strong effect for chronic offenders in Model III (Table 3). In contrast, the effect was negative and significant for Black offenders (Model IV) where, on average, a chronic offender had lower odds of receiving probation. In addition, having an accomplice was significant in the standard model but not for the Black male model (Models I and II). There was also evidence that the age of the offender influences the secure confinement decision. Models I and III demonstrate that in comparison with 16-year-old offenders, 14-year-old offenders’ odds of receiving secure confinement are much lower (Model I: b = −.419, p < .05; Model III: b = −.442, p < .05). Finally, we see that the offense significantly influences the confinement decision. For Criminal Sexual Conduct (CSC) offenses, the coefficients were significant across both the standard and Black offender models (Models I and II). Interestingly, Black sex offenders were at substantially higher odds of receiving secure confinement relative to White offenders (Model II). In Models III and IV, we also find that the type of offense has a significant effect on probation. For example, in Model III, all offense categories had a positive and significant effect on the probation decision. This was true for only criminal sexual conduct in the Black offender model (Model IV) where the odds of receiving probation are marginally reduced relative to similarly situated White offenders.

Among the Level 2 (county-level) predictors, several predictors were significant in both the standard model (Model I) and the Black offender model (Model II). Notably, “percent urban” was significant in both models; in Model II, Black offender’s odds of being sentenced to secure confinement were 1.011 (exp [.011]) times greater. We also observe that the size of the teenage population influenced the sentencing decision in the Black offender model (Model II), such that the odds of receiving secure confinement were 1.388 times (exp [.328]) greater for Black offenders. The effect of teenage population was considerably larger in Model IV where the odds of secure confinement were 3.23 times (exp [1.174]) greater for Black offenders. Percent Black population and Black population change also emerged as significant predictors in Models I and II. However, as seen in Model IV, percent Black population has a considerably stronger effect, in that the odds of Black offenders receiving probation were 1.21 (exp [.191]) times greater.

The analysis also revealed that concentrated disadvantage influenced the secure confinement decision. Specifically, the odds of receiving secure confinement were 1.25 times greater (exp [.230]) for Black offenders who lived in areas characterized by high levels of concentrated disadvantage. Thus, Model II suggests that some offenders may be doubly disadvantaged by both race and economics but it may not be that surprising, given the literature which suggests that concentrated disadvantage is a powerful driver of many criminal justice decisions (see Bontrager et al., 2005; Parker, Stults, & Rice, 2005; Thomas et al., 2013). However, there was no significant effect for concentrated disadvantage in Models III and IV. This finding may also accord with Rodriguez (2013) who found that concentrated disadvantage affects confinement but may make little difference for less punitive juvenile dispositions.

Discussion

The present study sought to use the racial threat perspective as an organizing framework for understanding the differences in the use of sanctions for juvenile offenders. Importantly, this research attempted to provide answers for whether both race and economic factors affect the decision to sentence juvenile offenders to secure confinement or some other sanction such as probation. In part, the racial threat perspective assumes that punitiveness increases (or decreases as this is a non-linear relationship) when minority populations increase in size, such that they are in direct competition with the dominant group for power and/or resources. The present research supports the basic tenets of the racial threat hypothesis.

Several key hypotheses are confirmed by the research. Our first hypothesis (H1) argued that minority offenders would be sentenced more severely compared with similarly situated White offenders. Findings showed that Black offenders face greater odds of being sentenced to secure confinement relative to their White counterparts, consistent with some prior research (Armstrong & Rodriguez, 2005; Bishop & Frazier, 1996; Bontrager et al., 2005; Rodriguez, 2013). This research found that as the size of the Black population increases, the punitiveness of sanctions also increases (H2). That is, the odds of any juvenile receiving secure confinement in counties with larger Black populations were greater. These findings are in line with Gold (2004) and a number of other scholars (Parker, Stults, & Rice, 2005; Taylor, 1998). In light of the fact that the size of the Black population may function as both an indicator of relative threat and dangerousness, the juvenile justice system may be thus freed to utilize more formal means of social control such as secure confinement facilities. Our confidence in this finding is also bolstered by the fact that we included an additional measure for the relative size of the Black population over time, Black population change, rather than rely on a single measure that is seen in much of the racial threat research (Eitle et al., 2002; Parker, Stults, & Rice, 2005).

We observed similar results in the probation models (Model IV) where percent Black population was significant only for the Black offender model and Black population change was significant in the Black offender model. That is, the odds of Black offenders receiving probation versus an alternative sanction in counties with an increasing Black population were greater. Perhaps these findings are not entirely surprising in light of the literature, which suggests that there is a penalty paid by young, Black males residing in areas of high and/or increasing Black populations (Caravelis, Chiricos, & Bales, 2011; Holleran & Spohn, 2004; Spohn & Holleran, 2000). Given these findings, one can surmise that there is strong evidence that racial threat plays a part in the use of sanctions for juveniles in this state.

Our third hypothesis (H3) was premised on how political power is manifested within the juvenile justice system. We conceived of political power not only in terms of the growth in minority populations (see Eitle et al., 2002) but also in terms of growth in arenas of power where minorities (both sex and race) have historically been underrepresented, specifically on the bench. With this in mind, we believed that as the number of racial minorities and women on the bench increased, there would be a concomitant increase in the punitive sanctions that were imposed on offenders who identified with these groups (see Ward, Farrell, & Rousseau, 2009a).

A variation of this argument was also posited by Yates and Fording (2005) who framed their argument in terms of party affiliation and responsiveness to “black interests.” We found some support for this hypothesis, in that minority judges exerted a marginal effect on reducing the odds that Black offenders would be sentenced to secure confinement (Model II). However, this effect was substantially greater in Model IV (Table 3) where the odds of probation were 1.98 (exp [.688]) times greater when there were minority judges on the bench. This finding seems to be in line with the research of Ward and colleagues (2009a) who noted the important role of diversity among criminal justice decision makers. Neither the secure confinement model nor the probation model showed any evidence that the presence of female judges made a difference in terms of the sanction use. Despite the equivocal nature of some of the research literature concerning the race of the judge (Coontz, 2000; Freiburger, 2010; Steffensmeier & Britt, 2001; Van Slyke & Bales, 2013), this research offers tentative support for the view that race matters with regard to the importance of bench diversity.

These findings also suggest that our understanding of the racial threat thesis may benefit from the development of a more nuanced view of political power. Just as minority defendants face substantial disadvantages based on their social and economic positions, or which result from the lack of representation at the municipal or legislative level, it is equally likely that they face similar disadvantages when there are power differentials with regard to those who are charged with interpreting and enforcing the law (Ward et al., 2009a; Ward, Farrell, & Rousseau, 2009b). As our findings suggest, political power on the bench matters in terms of the outcomes for Black offenders. The nature and reach of this political power require additional study.

Our analyses found support for H4 which stated that urbanization would affect the kind of sanction that juvenile offenders received. Offenders in Model II (Black offender with cross-level interactions) saw significantly greater odds in the decision to be sentenced to secure confinement compared with White juvenile offenders. This finding seems to align with the literature which suggests that there is a correlation between urbanization and sanction severity (Davis & Sorensen, 2013; DeJong & Jackson, 1998; Payne & Welch, 2010). This heightened incarceration risk for Black males may be driven by the perception that they are more dangerous than similarly situated White and Hispanic offenders (Bobo & Hutchings, 1996; Bontrager et al., 2005; King & Wheelock, 2007; Spohn & Holleran, 2000; Steffensmeier & Demuth, 2001; Wang, 2012). Moreover, the coupling of urbanization and public perception, augmented by racial stereotypes (Steen, Engen, & Gainey, 2005; Steffensmeier et al., 1998; K. Welch, 2007), seems to drive some sentencing decisions, and it underscores the need for stakeholders at all levels of the criminal justice system to take stock of how the confluence of societal and their own assumptions about race affect crime control policies. To the extent that stakeholders become more aware and confront their own unconscious biases (Graham & Lowery, 2004), the punishment gap between Black males and other offenders (both adult and juvenile) will be substantially reduced.

Finally, we found that concentrated disadvantage shapes the use of sanctions for Black juveniles. Many scholars presume that where increased levels of concentrated disadvantage (inequality) exist, we should expect to see a concomitant increase in the use of punitive criminal justice policies, sanctions, or other negative outcomes (Rodriguez, 2013; Sampson, Morenoff, & Earls, 1999). We found some support that concentrated disadvantage affects the use of sanctions, in that Black offenders were sentenced more often to secure confinement than their White counterparts (Model II). We also found that concentrated disadvantage did not significantly affect the use of probation (Models III and IV). Overall, these findings with regard to concentrated disadvantage suggest that economic factors may play an important, yet limited, role in the calculus used by decision makers to determine sanctions.

Conclusion

There are a number of important implications that can be drawn from this study. First, the results of this research suggest that juvenile justice stakeholders need to pay closer attention to the link between economics (concentrated disadvantage) and sanctions. Just as there is concern that race and ethnicity may unfairly disadvantage juvenile offenders, there should be equal concern that one’s economic circumstances do not erect barriers to consistent and fair treatment in the juvenile court. Justice Hugo Black famously said that “the kind of trial that a man gets should not depend on how much money that he has” (Griffin v. Illinois, 1956). This observation seems equally applicable with regard to how offenders, especially Black offenders, are sanctioned by the courts. Our results suggest that Black juveniles may be doubly disadvantaged, by their economic situation and by their race, with regard to the use of sanctions. There should be a continuing effort in the empirical literature to ferret out how pernicious and destructive both race and economics can be in criminal justice decision making.

The findings reported here also have several implications for how scholars discuss the influence of race, concentrated disadvantage, and other contextual factors on juvenile court adjudications. The results show that minority defendants are more likely to receive more severe dispositions compared with White defendants. That said, it is possible that juvenile court judges, at the adjudication stage, view minority offenders as more dangerous and less rehabilitative than other White juvenile offenders. Given the level of uncertainty often seen at the adjudication phase due to the lack of information about the true extent of an offender’s past (or their true potential to become better versions of their current selves), juvenile court judges may be exceedingly cautious and averse to taking chances that ordinarily would result in a much less severe sanctions (Albonetti, 1986; Bridges & Steen, 1998). It is also possible that because these judges are cautious and averse to uncertainty that they retreat to racial stereotypes to augment the sometimes limited information that they have about juvenile offenders. Accordingly, as these findings would seem to suggest, the offending of Black offenders is deemed more serious, and it activates a much harsher and perhaps much more meaningful juvenile court response.

In addition, it is possible that offenders’ race tap into a dimension of unconscious stereotyping and bias existent among juvenile court judges (Lawrence, 1987; Quillian, 2008).¹⁴ This observation is not suggesting that judges in this state are racially biased, but rather, judges are largely unaware of the degree to which their cultural beliefs influence and shape how they view race and their beliefs about race (Lawrence, 1987). As applied to the juvenile court, judges may believe that they are applying the law or making sentencing decisions in a racially neutral manner. However, it is likely that their decision making “transmits beliefs and preferences” about the law and peoples’ place within the legal order (Leiber, Bishop & Chamlin, 2011, p. 323). As such, juvenile court judges may be more inclined to see Black offenders as dangerous, hostile, or threatening. Sentencing these offenders to secure confinement, then, can be justified because the offenses they have committed are consistent with the stereotype. Unfortunately, constructing and testing measures of unconscious bias could not be accomplished in this study.

This observation also has implications for disproportionate minority contact (DMC). DMC is a real issue problem in the juvenile justice system as evidenced by the fact that minority youth disproportionately come into contact with the juvenile justice system relative to their numbers in the general population. Explanations range from differential offending to macrocontextual issues (Engen et al., 2002). Although there may not yet be a consensus on the cause, the evidence seems to be pretty clear that it is a problem in juvenile justice (cf. Cabaniss, Frabutt, Kendrick, & Arbuckle, 2007; Huizinga et al., 2007).

Also, it is possible that DMC can be addressed by reducing the number of risk factors for contact (Huizinga et al., 2007). Consistent with other research, the findings here suggest that concentrated disadvantage is one of the strongest risk factors associated with secure confinement dispositions (see also Kubrin & Stewart, 2006; Rodriguez, 2013). Given this finding, it is important that juvenile justice stakeholders begin to grapple with the myriad ways in which socioeconomic status and race are entangled, especially as it relates to “juveniles in need of supervision” and “juveniles who are not receiving adequate care at home.” While it is true that a range of services should be provided to juveniles who need them, it is equally true that restraint should be exercised regarding the reach of the juvenile justice system, such that offenders who are identified as “in need” of services are not unnecessarily drawn within the ambit of the juvenile justice system (Leiber et al., 2011). This tension may in part explain why African American offenders in this state receive more severe juvenile court dispositions.

Finally, if DMC is the product of unconscious bias then the possibility for truly finding a solution to the overrepresentation of minority youth in the juvenile justice system may be beyond our reach. However, Cabaniss et al. (2007) do suggest one interesting approach by way of cultural competency training. Among other things, cultural competency training teaches juvenile justice actors how to recognize, identify, and combat racial and ethnic stereotyping and how such biases affect juvenile justice outcomes (Cabaniss et al., 2007). As noted earlier, remedying unconscious bias is very difficult; however, the only solution to DMC may require that all stakeholders continually take stock of and acknowledge that such biases exist (cultural competence) and develop strategies to ensure that they do not continue to perpetuate racial and ethnic disparities among juvenile offenders.

Notwithstanding the significance of the findings, there remain a few limitations in the research that should be pointed out. Although statewide data were used, we were unable to include a separate and meaningful analysis for Hispanic offenders because of their small number in the sample (n = 38). Nevertheless, the Hispanic population is the fastest growing population in the state and comprises about 5% of the state’s population (as of 2013). Given this, future research should endeavor to include some measure of the Hispanic population as an important comparison group. Second, we conceived of political power in terms of diversity on the judicial bench. While we did uncover some interesting patterns in the results, it may have been useful to have some measure for percent female judges and percent Black judges. The inclusion of such measures would have perhaps enabled us to determine whether there is some threshold at which the race and sex of the judge begin to exert a protective effect on juvenile offenders. Third, this research analyzes data at only one decision point in the juvenile justice system. However, information prior to the adjudication stage was not available to these researchers. Recognizing the importance of gathering data from multiple points in the process (Leiber et al., 2011), we believe that some important insights are gained by understanding the “back-end stage” of juvenile justice processing. If it is true that corrective measures sometimes occur on the “back-end” of the process (back-end mitigation) to ameliorate some of the biases and harshness that occurs on the “front-end” of the system, then shining a light on this exit point is equally important as understanding the point of entry for juvenile offenders. Last, the inability to ferret out the extent to which other sanctions such as community service are used places an important limitation on what this research can truly say about the racial threat hypothesis.

In the end, this research is an important step in furthering our understanding of how race and concentrated disadvantage affect outcomes for juvenile offenders. Other scholars with an interest in the racial threat hypothesis should endeavor to extend this research by refining how political power is measured. In addition, it would behoove future researchers to continually refine their use of county-level indicators of racial threat if research in this area is to move forward.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Patrick G. Lowery is an assistant professor in the L. Douglas Wilder School of Government and Public Affairs at Virginia Commonwealth University. He received his PhD from the University of South Carolina. His primary research interests and publications lie in juvenile justice, inequalities, race/ethnicity, and police violence. He has previously published in Youth Violence and Juvenile Justice and Police Quarterly.

John D. Burrow, PhD, JD, is an associate professor in the Department of Criminology and Criminal Justice at the University of South Carolina. He received his PhD from Michigan State University and received his JD from the University of Wisconsin. His research interests include sentencing, race and crime, juvenile delinquency, law and justice, and children’s rights. His research has appeared in a number of scholarly journals, including Crime & Delinquency, Justice Quarterly, and Youth Violence and Juvenile Justice.

Robert J. Kaminski is an associate professor in the Department of Criminology and Criminal Justice, University of South Carolina. He earned his PhD from the University at Albany, State University of New York. His research has appeared in a variety of scholarly journals, including Criminology, Crime and Delinquency, the Journal of Quantitative Criminology, and Justice Quarterly.

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