Data have shown that youths of color are more likely than white youths to be arrested and subsequently go deeper into the juvenile justice system (e.g., Puzzanchera, 2021; Puzzanchera and Hockenberry, 2013; Sickmund et al., 2021; Sickmund, Sladky, and Kang, 2021). Researchers have examined the contributing factors to these racial and ethnic disparities for decades, often testing hypotheses and theoretical frameworks related to differential offending and system biases (Leiber and Fix, 2019; Pope and Feyerherm, 1990; Pope, Lovell, and Hsia, 2002; Zane and Pupo, 2021). Most scholars acknowledge there are numerous factors at work and that this complex social problem cannot be reduced to either differential offending or differential treatment alone (National Research Council, 2013). Much of the work to address racial and ethnic disparities in the juvenile justice system has been driven by amendments to the federal Juvenile Justice and Delinquency Prevention Act (JJDPA) through the federal Office of Juvenile Justice and Delinquency Prevention (OJJDP). Although some progress has been made and overall involvement in the juvenile justice system has been decreasing nationally, disparities continue to exist today, especially for Black and American Indian/Alaska Native youths (see Figures 1, 2a, and 2c).
This literature review covers racial and ethnic disparities in the juvenile justice system. It begins with definitions related to racial and ethnic disparities, which are followed by how disparities can be measured and a description of the scope of the problem. A brief history of the Core Requirement to address racial and ethnic disproportionality in the JJDPA is then presented, followed by a description of a large body of empirical studies that attempt to explain why there are disparities in juvenile justice. A brief overview is provided on some of the efforts to address racial and ethnic disparities that have been captured by research literature, followed, finally, by examples of programs related to the reduction of these disparities.
Terminology related to racial and ethnic disparity has changed over time. According to the JJDPA, amended in 2018, racial and ethnic disparity means minority youth populations are involved at a decision point in the juvenile justice system at disproportionately higher rates than nonminority youth at that decision point (Pub. L. 115–385, title I, § 102) and is often written as R.E.D., RED, R/ED, or ERD. From 2002 to 2018, OJJDP referred to this as disproportionate minority contact (DMC). Before that, DMC stood for disproportionate minority confinement. Confinement was changed to contact in 2002 because of disproportionality throughout all stages of the juvenile justice system (e.g., arrest, diversion, probation), and not merely at confinement (OJJDP, 2009a).
The terms disproportionality and disparity often are used interchangeably to refer to rates of contact with any point of the juvenile justice system that are not the same among different races or ethnicities, regardless of the cause. However, their meanings differ slightly: disproportionality refers to the state of being out of proportion, while disparity refers to a state of being unequal (Abrams, Mizel, and Barnert, 2021; Dettlaff et al., 2011).
The term minority overrepresentation is still used by some organizations but increasingly has been replaced by either the term disparity or disproportion since minority youths often are underrepresented in receiving more -lenient outcomes such as diversion from court and probation placement after a finding of delinquency.
Juvenile justice contact points or decision points are terms used to refer to different points where youths have “contact” with the juvenile justice system (e.g., arrest, detention, petition). These two terms are frequently used interchangeably but referring to these stages as decision points shifts greater attention on the juvenile justice system decisionmakers who determine whether the youths will become involved in the system at that point.
Discrimination denotes between-group differences in outcomes based on the consideration of extralegal or illegitimate factors (Bishop, 2005). The terms discrimination and bias are used when disparities appear to be caused by some intent on the part of the decisionmaker or when a system’s design puts minority youth at a disadvantage. Both individual and system bias can be intentional but often are unintentional or implicit (Fix, 2020; Goff et al., 2014; Gove, 2011; Tomaskovic–Devey and Warren, 2009).
Disproportionality can be measured using various approaches, such as comparing proportions or using rates. Each of these measures identifies levels of disproportionality in a specific way.
- Proportions. When using proportions, the racial breakdown of youths in the general population is usually compared with the racial breakdown of youths at a certain point in the juvenile justice system. For example, someone may explain that while only 15 percent of all youths in the United States are Black, 41 percent of juveniles in the population committed to residential placement are Black, indicating racial disparities (Rovner, 2021a). Proportions at one point can also be compared with the proportions in the preceding point (or points) to see incremental changes. For example, one publication compared the representation of Black youth in the general population with five stages of the justice system (arrests, referrals to court, detention, residential placement, admission to adult prison), demonstrating their increasing involvement in the justice system in Pennsylvania (Shoenberg, 2012). In this case, Black youths made up less than 20 percent of the youth population but more than 25 percent of the arrests, more than 30 percent of the referrals, slightly less than 40 percent of the detained and placed youths, and almost 60 percent of the youths admitted to adult prison. There are some limitations to using proportions. It can be difficult to use proportions to compare disparities in different jurisdictions or to examine trends over time when the composition of the youth population changes (Feyerherm and Butts, 2002; Feyerherm, Snyder, and Villarruel, 2009). Also, when minority groups are in the majority (i.e., when most youths in a population are nonwhite), disparities may appear less evident than when using rates.
- Relative Rates. Another approach to measuring disproportionality is to use the relative rate index (RRI). The RRI compares the rates of processing for minority youth with the rates of processing for white youth. The RRI method describes the volume of activity from one contact point to the next and how it differs between white and minority youths, thereby isolating disproportionality at a particular point (e.g., comparing secure detention rates among the population of youth referred to court) (Feyerherm and Butts, 2002; Feyerherm, Snyder, and Villarruel, 2009). The RRI can also be based on the general youth population (e.g., comparing the incarceration rate based on the general youth population). Thus, as with using proportions, the RRI can consider the rates of processing at the previous point or compare rates from the general youth population.
- Rates. Rates and relative rates can show different aspects of disproportionality. For example, the Census of Juveniles in Residential Placement provides the counts, percentages, and rates of youths in custody per 100,000 in the population. In the most recent census, Massachusetts had one of the lowest rates of residential placement for Black juveniles (133 per 100,000). However, because the rate for white juveniles in Massachusetts (19 per 100,000) was much lower than the Black rate, the Massachusetts' RRI is higher than the national average of 4.4 (see Figure 2a), indicating high levels of disproportionality in the state. By contrast, Indiana had one of the lowest population-based RRIs for Black youth, even though they had higher residential placement rates for Black youth than Massachusetts. Since the residential placement rate for Black youths in Indiana (298 per 100,000) was closer to the rate for white youths in Indiana (138 per 100,000), it had a much lower RRI than Massachusetts (RRI of 2.2 in Indiana compared with 7.0 in Massachusetts) but still a higher placement rate for Black youths than Massachusetts (Sickmund et al., 2021).
Counts, rates, proportions, and RRIs all direct policymakers and practitioners to the points of the juvenile justice system that may need more examination, but none of these measures identifies contributing mechanisms for this disproportionality (Hsia et al., 2006). Each of these measurement approaches has been used at different times by OJJDP (Harp, 2018; Leiber and Fix, 2019) and within the research literature (e.g., Leiber and Fix, 2019; Abrams, Mizel, and Barnert, 2021; Rovner, 2021b), as each measure provides unique information that is valuable for recognizing and monitoring disproportionality. As of 2019, OJJDP no longer accepts RRI to demonstrate compliance with the Core Requirement (see "Federal Legislation" section below).
National data show that Black youths and other youths of color are more likely than white youths to be arrested, referred to court, petitioned after referral (i.e., handled formally), and placed in an out-of-home facility after being adjudicated (Hockenberry and Puzzanchera, 2020; Sickmund, Sladky, and Kang, 2021.).
In 2019, compared to white youths, Black youths were 2.4 times more likely and American Indian youths were 1.5 times more likely to be arrested. On the other hand, Asian youths were less likely than white youths to be arrested (OJJDP, 2020).
Juvenile court data generally provide more detail than arrest data, including information for Hispanic youths. In 2018, 52 percent of delinquency cases involving white youths in juvenile court were handled formally (instead of being handled informally—that is, without filing a petition for adjudication, such as through diversion), compared with 64 percent of cases involving Black youths, 58 percent of cases involving American Indian youths, 55 percent of cases involving Hispanic youths, and 54 percent of cases involving Asian youths. Also, after being adjudicated delinquent, cases involving Black juveniles and Hispanic juveniles were more likely to result in out-of-home placements (32 percent each) than cases involving youth of all other races/ethnicities (27 percent of cases involving American Indian juveniles, 23 percent of cases involving white juveniles, 20 percent of cases involving Asian juveniles) (Hockenberry and Puzzanchera, 2020:58–59).
However, although Black youths tend to be pushed further into the system at most juvenile justice decision points than youths of other races/ethnicities, this is not always the case. Among cases handled formally in juvenile court, American Indian youths were the most likely to be adjudicated delinquent (59 percent), followed by Hispanic youths (57 percent), white youths (52 percent), Asian youths (49 percent), and finally Black youths (49 percent) [Hockenberry and Puzzanchera, 2020]. Similarly, a systematic review of empirical studies examining racial disparities in juvenile justice found that the adjudication decision was the least likely to show disadvantage toward youth of color, including Black youth (Spinney et al., 2018).
The previous two paragraphs describe disparities at each point, as youths move from one juvenile justice contact point to another. Point-in-time estimates at the deep end of the system can also demonstrate the prevalence of disparities relative to the whole population. For example, in 2019, the Census of Juveniles in Residential Placement showed a rate of 315 Black youths in custody per 100,000 in the population, compared with 72 white youths per 100,000—a ratio of approximately 4.4 to 1.0 (Sickmund et al., 2021), which is the same as a population-based RRI of 4.4 (see Figure 2a). Data collected for Hispanic and American Indian youths have also indicated higher levels of placement than white youth, although these disparities have lessened for Hispanic youths (see Figure 2b) over time (Sickmund et al. 2021).
Nationally, the rate of juveniles in residential placement decreased from 356 per 100,000 in 1997 to 114 per 100,000 in 2019 (Sickmund et al., 2021). During this time, the residential placement rates decreased for all youth races (see Figure 1). However, disparities have not decreased in the same way for all. While it appears that disproportionality in residential placement has decreased for Hispanic youths, compared with white youths (as measured with a decreasing RRI from 2.3 in 1997 to 1.3 in 2019; see Figure 2b), it has remained relatively steady for Black youths (ranging from 3.9 to 5.0 since 1997; see Figure 2a). Disproportionality for American Indian youths appears to be increasing (see Figure 2c). Asian youths were less likely than white youths to be in a residential placement each year from 1997 to 2019, and this relative rate has deceased consistently from almost 1.0 in 2007 to about 0.25 in 2017 and 2019 (see Figure 2d).
Although these national rates provide an important snapshot, disparities vary from state to state, jurisdiction to jurisdiction, among different offense types, and by other demographics. For example, the Census of Juveniles in Residential Placement provides juvenile placement rates by state and race, which demonstrate large differences in disproportionality: the population-based RRI for Black youth in New Jersey, New Hampshire, and Wisconsin is over 10.0, while it is less than 3.0 in Alabama, Indiana, New Mexico, and Wyoming; the population-based RRI for Native American youth is more than 10.0 in Nebraska and less than 1.0 in New Mexico, Nevada, and Texas (Sickmund et al. 2021).
State studies also find differences in disproportionality by jurisdiction. For example, Michigan data collected by the Michigan Committee on Juvenile Justice show that Black youths were statistically significantly less likely to be securely detained than white youths in Kent County, but there was no statistically significant difference in Oakland County (Michigan Committee on Juvenile Justice, 2021). Similarly, a DMC assessment study of Tennessee found that two major metropolitan areas had statistically significantly higher levels of disparities for Black youth, compared with rural areas of the state (Tennessee Commission on Children and Youth, 2012:64).
In terms of gender, state and national data show some differences in levels of disparity, although consistent trends have not emerged. For example, data from Florida show that statewide racial disparities are greater for Black boys than for Black girls at the arrest stages (RRI of 3.3 for Black boys and 2.6 for Black girls) and at the diversion stage (RRI of 0.7 for Black boys and 0.9 for Black girls) [Florida Department of Juvenile Justice, n.d.]. But racial disparities were the same for boys and girls in Florida at detention (RRI of 1.4 for both genders). Also, a Virginia study found that gender composition of racial/ethnic groups in Norfolk County varied among youth referred to juvenile court: 46 percent of the Hispanic youths referred to court were girls, compared with 39 percent of white youths and 36 percent of Black youths (Harig et al., 2012). Finally, a Nebraska study found that for white, Black, and Hispanic youth, males were statistically significantly more likely to be taken into custody than females, but for Native American youth, females were more likely to be taken into custody than males (Hobbs et al., 2012).
National data showing racial and ethnic compositions at various points of the juvenile justice system also demonstrate some differences by gender. For example, in the population of boys in residential placement in 2019, 33 percent were white, and 42 percent were Black; in the population of girls, 38 percent were white, and 35 percent were Black (Sickmund et al., 2021). Similarly, juvenile court data demonstrate differences in gender composition for certain charges. For example, among girls with drug charges in 2019, 61 percent were white, while 39 percent were minority; among boys with drug charges, 51 percent were white, while 49 percent were minority (Sickmund, Sladky, and Kang, 2021). However, for person offenses, the portion of the sample that was minority was higher for the boys than for the girls (58 percent, compared with 61 percent).
Finally, racial disparities vary by offense type. Arrest data from the Federal Bureau of Investigation (FBI) show that both arrest rates and relative rates differ by offense. For example, Black youths were eight times more likely than white youths to be arrested for stolen property (buying, receiving, possessing) and seven times more likely to be arrested for robbery. However, they were less likely than white youths to be arrested for drunkenness, liquor laws, and driving under the influence. American Indian youths were six times more likely than white youths to be arrested for offenses against the family and children and five times more likely to be arrested for drunkenness, but they were less likely than white youths to be arrested for gambling, robbery, embezzlement, prostitution and commercialized vice, and forgery and counterfeiting. Offense types among the residential population also differ by race. Further, according to the Census of Juveniles in Residential Placement, although all races/ethnicities were most likely to be in residential placement for a person offense (35.7 percent) or a property offense (26.0 percent), white and Native American youths were overrepresented among status offenders (Sickmund et al., 2021).
At the diversion stage, an RRI lower than 1 indicates disproportionality disadvantaging minority youth, since being diverted is a positive option.
Over the years, amendments to the federal JJDPA of 1974 and OJJDP compliance requirements for states applying for and/or receiving JJDPA Formula Grant funding have provided direction on how states address racial and ethnic disparities. These amendments occurred in 1988, 1992, 2002, and 2018.
First, the 1988 JJDP Act amendment contained a requirement that states address DMC (which at this point meant disproportionate minority confinement) in their state plans. Then, in the 1992 amendment, the identification of DMC became a Core Requirement, tying state compliance to future funding through the Formula Grants Program (OJJDP, 2013; OJJDP, n.d.a; OJJDP, n.d.b). Requirements in subsequent amendments were also tied to Formula Grant funding.
Amendments in 2002 resulted in a requirement that states, "address juvenile delinquency prevention efforts and system improvement efforts designed to reduce, without establishing or requiring numerical standards or quotas, the disproportionate number of juvenile members of minority groups, who come into contact with the juvenile justice system" (Pub. L. No. 107–273, 116 Stat. 1878 (23)). Between 2002 and 2018, states were required to submit data to OJJDP on the numbers of youths by race/ethnicity who came into contact with nine juvenile justice system points statewide, and for at least three targeted counties in the state. The nine juvenile justice points were 1) arrest (law enforcement referral), 2) referral to court, 3) diversion, 4) secure detention, 5) petition filed (charged), 6) adjudication (delinquent, guilty finding), 7) probation supervision, 8) secure confinement, and 9) transfer to adult court (waiver).
OJJDP outlined a five-stage process for states to follow: 1) identify the extent to which DMC exists, 2) assess the reasons for DMC, 3) develop an intervention plan to address DMC, 4) evaluate the effectiveness of interventions, and 5) monitor DMC trends (OJJDP, 2009a). During this time, DMC was measured using the RRI.
In December 2018, the Juvenile Justice Reform Act was signed into law, again reauthorizing the JJDPA and amending certain parts of the Act. The amendments became effective on Oct. 1, 2019 (OJJDP, 2019b). The requirement to "address DMC" was changed to "identifying and reducing racial and ethnic disparities" (OJJDP, 2019a). Other changes included a reduction in the number of decision points where states are required to track data, from 9 points to 5 points (OJJDP, 2019c), "where research has shown that potential disparity may occur":
- Diversion [filing of charges]
- Pretrial detention
- Disposition commitments
- Adult transfer [OJJDP, n.d.c]
OJJDP also began requiring that states measure disparities by using proportions instead of relative rates and that they submit plans with three-pronged strategies. The three prongs are to 1) submit statewide data for at least four of the five juvenile justice contact points (indicated above), by providing the percentage distribution of race or ethnic groups compared with the general population distribution, 2) develop an action plan to reduce racial and ethnic disparities, and 3) conduct an outcome-based evaluation by tracking changes in numbers, addressing whether goals were met, indicating what worked and what drove that success, identifying barriers to success, indicating how OJJDP can help, explaining how they will protect the public and hold offenders accountable, and forming goals for the following year (OJJDP, n.d.c).
Numerous national and jurisdiction-specific studies on racial and ethnic disparities have been conducted. These empirical studies differ from those that focus solely on rates, counts, and proportions because empirical studies attempt to better understand why the disproportionality is occurring. Between 2002 and 2018, OJJDP distinguished between these two stages, with the former being the "identification stage" and the latter being the "assessment stage."
Many of these empirical studies examine whether race had an effect on one or more juvenile justice decision points after controlling for other variables (e.g., offense severity, prior record, age, gender). Many of these studies are guided by research interests and are published in scholarly journals (e.g., Abrams, Mizel, and Barnert, 2021; Rodriguez, 2007; Leiber, Brubaker, and Fox, 2009; Freiburger and Burke, 2010; Zane, Mears, and Welsh, 2020), while another group of studies resulted from the OJJDP mandate for states to conduct DMC assessment studies and are generally published as reports available to the public (Donnelly and Asiedu, 2021).
Several large-scale, comprehensive efforts have been conducted that analyzed the body of research literature on racial and ethnic disparities in juvenile justice (Pope and Feyerherm, 1990; Pope, Lovell, and Hsia, 2002; Engen, Steen, and Bridges, 2002; Bishop, 2005; Bishop and Leiber, 2012; Spinney et al., 2018; Zane and Pupo, 2021). For example, one of these reviews (Spinney et al., 2018) was an OJJDP–funded review of articles from 2002 to 2014 evaluating the percentage of studies that found disparities, by decision point and by race/ethnicity. This study found that, while the picture that emerges collectively is complex, effects of race that disadvantage minority youths were found to exist at all decision points. This finding is similar to the results of other reviews, which found that race affects decisionmaking to some extent but also that other legal variables (such as prior offense and offense seriousness) and extralegal variables (such as age) also play key roles (Pope and Feyerherm, 1990; Pope, Lovell, and Hsia, 2002; Engen, Steen, and Bridges, 2002; Bishop, 2005; Bishop and Leiber, 2012; Zane and Pupo, 2021). The degree of these disparities can vary considerably by both decision point and race/ethnicity.
First, the extent of disparity varies across points in the process. For example, in the 2018 review by Spinney and colleagues described above, studies that included analysis of earlier decision points in the juvenile justice system (e.g., arrest, secure detention, and referral to court) overwhelmingly found there was some disadvantage to minority youths. However, fewer studies of later decision points (e.g., adjudication, probation, secure confinement, and disposition in adult court for transferred youths) found racial disadvantage to minority youths.
Second, levels of disparity at each point in the system vary by racial and ethnic group. A more-recent systematic review used meta-analytic techniques to analyze the data from studies of racial disparities. This review found there was a small average effect for some outcomes (e.g., detention) and no discernible average effect on others (e.g., petition, waiver, adjudication). Specifically, the authors found that
- For Black/white comparisons, there was evidence of small average race effects on detention and placement, a slight average effect on intake, and no average effects on petition, waiver, or adjudication.
- For Hispanic/white comparisons, there was evidence of a small average race effect on detention; slight average effects on petition, adjudication, and placement; and no average effects on intake or waiver.
- For nonwhite/white comparisons, there was evidence of small average effects on detention, intake, and waiver; a slight average effect on placement; and no average effect on petition or adjudication. [Zane and Pupo, 2021]
However, even small average race effects can make a large impact over the course of the many decisions in the juvenile justice system through cumulative disadvantage (Kurlychek and Johnson, 2019; Pope and Feyerherm, 1990; Zane, 2018). Cumulative disadvantage can be displayed in at least two different ways. First, simple accumulation occurs when a higher rate of arrest for minority youth is subsequently followed by a lower rate of diversion, higher rates of formal processing as delinquent, and so forth (Pope and Feyerherm, 1990; Spinney et al., 2018). Thus, although the differential treatment at any particular stage may appear "small," the cumulative impact across the entire juvenile justice system may be relatively large. Second, decisions made at earlier stages, such as detention, can affect outcomes at later stages—in particular, judicial disposition (Leiber and Fox, 2005; Mendel, 2014; Rodriguez, 2010). For example, one study of predictors of formal disposition in a large southern state found that the number of days spent in secure detention predicted formal disposition even after controlling for offense type, gang affiliation, weapon carrying, and extralegal factors (Caudill et al., 2013). However, minority youths are more likely to be detained than their white counterparts. Thus, although minority youths and white youths who have been detained may be treated similarly, because the minority youths are more likely to be detained, they are also more likely than to receive more severe dispositions than do their white counterparts.
An emerging body of literature has examined additional discretionary decisions. For example, a systematic review of 26 studies examining racial disparities among referrals to mental health and substance misuse services from within the juvenile justice system found that the majority of studies showed at least some race effects in the decision to refer youths (Spinney et al., 2016). Another study (Ogle, 2019) examined whether there were racial and ethnic disparities in the use of solitary confinement among pre-adjudicatory youth in juvenile detention centers in Florida, finding that Black youths had 68.8 percent greater odds of being placed in solitary confinement than white youths, even after incorporating statistical controls for relevant factors such as risk to reoffend. Researchers also have examined other decision points, including failure to appear for court hearings (Walker et al., 2019), probation violations (Gale–Bentz, 2019; Leiber and Peck, 2013), and being written up for new offenses while institutionalized (Oglesby–Neal and Peterson, 2021). Similarly, some researchers have examined racial disparities in pathways into the juvenile justice system, specifically in referrals from schools (Blad and Harwin, 2017; Hughes, Raines, and Malone, 2020).
Often racial and ethnic disparity is presented as being caused by differential offending (i.e., youths of color commit more crimes or commit more serious crimes) or differential treatment (i.e., the juvenile justice system treats youths of color differently). Differential offending is also referred to as differential involvement or differential behavior, and differential treatment is also referred to as differential selection or systems factors. These two theoretical frameworks have largely helped frame discussions and studies (Bishop, 2005), for these key theoretical distinctions suggest independent causal mechanisms that account for racial and ethnic disparities (Zane and Pupo, 2021).
The differential offending framework centers on the individual and refers to differing rates at which youths from various racial and ethnic subgroups are involved in delinquent activity. Differential behavior results when minority youths are involved in more serious crime, participate more deeply in gang activity, begin delinquent activity at earlier ages, and are involved in other social service– or justice-related systems such as the child welfare system (Leiber, Richetelli, and Feyerherm, 2009). This perspective requires that causes of differential involvement be sought outside the court system by looking at individual, family, and neighborhood factors that are related to offending (e.g., Piquero, Moffitt, and Lawton, 2005; Tracy, 2005). For example, Fite, Wynn, and Pardini (2009) found that much of the difference in arrest rates between white and Black boys was attributable to higher levels of both individual and contextual risk factors for Black boys across multiple domains.
In this framework, legal factors are often related to "minority-centered contexts of risk" (National Research Council, 2013:224), such as
- Economically disadvantaged and unstable communities and neighborhood social contexts (Fite, Wynn, and Pardini, 2009; Sampson, Morenoff, and Raudenbush, 2005; Moak et al., 2012)
- Low-performing institutions, especially public schools (Hirschfield, 2018; Sharkey and Sampson, 2010)
- Delinquent peers (Fite, Wynn, and Pardini, 2009; Haynie and Payne, 2006)
- Family risk factors such as unmarried or single parents, incarcerated parents, poor parent– child communication, death of a parent, and harsh, lax, or inconsistent discipline (Fite, Wynn, and Pardini, 2009; Jarjoura et al., 2013; Maguire–Jack, Lanier, and Lombardi, 2020; Sampson, Morenoff, and Raudenbush, 2005; Vespa, Lewis, and Kreider, 2013)
- Greater exposure to violence (Kilpatrick, Saunders, and Smith, 2003; Maguire–Jack, Lanier, and Lombardi, 2020)
Further, the allocation of prevention and treatment resources within communities is seldom uniform or universally accessible across an entire community. In some instances, those allocations create a disadvantage for minority youth (Leiber, Richetelli, and Feyerherm, 2009). For example, effective programs may be geographically inaccessible to minority youth in a jurisdiction, or existing programs may be designed for white, suburban youth. Thus, retention and outcomes for minority urban youth are weak. The National Research Council concluded that the “totality of these risk factors is such that minority youths are born into and raised in severely compromised familial, community, and educational environments that set the stage for a range of adverse behaviors and outcomes, including problems in school, relationships, and engaging in prosocial behavior” (2013:224).
The differential treatment framework perspective, by contrast, generally concentrates on the structure of justice decisionmaking acts that can disadvantage minority youth (e.g., Leiber, 2003; Pope and Feyerherm, 1990). This perspective, also known as bias theory, argues that minority youths are more likely than white youths to suffer harsher consequences at each stage of the juvenile justice decisionmaking process because the system treats minority youths differently (and more punitively). This theoretical orientation expects to find differential treatment of minority youth even after accounting for legal, and often extralegal (e.g., age, socioeconomic status, school status), factors (e.g., Mallett and Stoddard–Dare, 2010). The differential treatment framework centers on the juvenile justice system to explain disparities and is the approach that most frequently characterizes empirical studies of racial and ethnic disparities (e.g., Leiber, 2003; Leiber, Brubaker, and Fox, 2009; Richetelli, Hartstone, and Murphy, 2009).
A contributing factor related to differential treatment is justice by geography (Leiber, Richetelli, and Feyerherm, 2009). Minority youths may live in jurisdictions that have stricter law enforcement or harsher judges, compared with jurisdictions where white youths live (Bray, Sample, and Kempf–Leonard, 2005; Leiber, Richetelli, and Feyerherm, 2009; Taylor et al., 2012). For example, a Massachusetts DMC assessment study found that police tend to patrol urban minority neighborhoods more aggressively than suburban areas where fewer minorities reside. Thus, the likelihood of arrest is much higher for minority youth than white youth in this state (Kaufman, 1997).
Another explanation for differential treatment includes legislation, policies, and legal factors (Leiber, Richetelli, and Feyerherm, 2009). Policies enacted through legislation or administrative action may sometimes contain elements that create a disadvantage for minority youth. For example, statutes that define drug offenses tend to treat crack cocaine more seriously than powdered cocaine, which, given the usage patterns for the two forms of cocaine, creates a disadvantage for minority youth (Birckhead, 2017; Leiber, Richetelli, and Feyerherm, 2009). Zero-tolerance policies and other harsh discipline practices in school also adversely affect students of color (Dunbar and Villarruel, 2004; Hirschfield, 2018).
Differential processing or inappropriate decisionmaking is another contributing mechanism that can explain differential treatment. Differential processing or inappropriate decisionmaking results when the criteria used to make decisions in the system are either not applied consistently across all groups of youth or when the criteria are structured in a manner that disadvantages some groups. One example of differential processing or inappropriate decisionmaking is the use of the term gang related, which is cited frequently as a factor in decisions about how to handle juveniles. To assess gang-related impact, it is important to know how a jurisdiction defines the term and whether the “gang related” question is asked only of youth from certain communities. If so, then use of this criterion likely will place minority youth at some disadvantage relative to white youth—especially white youth from community areas not believed to be gang affiliated (Birckhead, 2017; Leiber, Richetelli, and Feyerherm, 2009). Another example is related to parenting structure. Some courts, fearing lack of supervision, may be more likely to use secure detention if the child is from a single-parent home. If minority youths are more likely to live in single-parent homes (Vespa, Lewis, and Kreider, 2013), these decisions will contribute to disparities (Leiber, Richetelli, and Feyerherm, 2009), regardless of the family’s ability to supervise their child.
Another contributing factor that has increasingly gotten more attention is implicit bias and its role in the many decisions made about juveniles as they move through (or are diverted from) the juvenile justice system (Darling–Hammond, 2017; Glenn, 2019; Marsh, 2009; National Juvenile Justice Network, 2017). Whereas explicit bias is a conscious preference (positive or negative) for a social category, implicit bias is a preference (positive or negative) for a social category that operates outside of awareness (Marsh, 2009). Although the research focused on exploring the link between implicit bias and racial and ethnic disparities in juvenile justice is limited (Glenn, 2019), many of the interventions aimed at reducing discretion in judicial decisionmaking are based on the belief that this discretion is influenced by bias, and more specifically by implicit bias. These interventions include two main approaches: 1) the use of risk assessment instruments (see below) and 2) trainings designed to reduce implicit bias among justice system decisionmakers by targeting implicit bias itself (e.g., Fix, 2020; Worden et al., 2020).
In addition to these examples of how differential treatment may occur, there are several related academic theories that may also explain differential treatment. The racial or symbolic threat theory (Ousey and Lee, 2008; Moak et al., 2012), within the differential treatment framework, focuses on the social–psychological processes behind decisions that disadvantage one or more racial/ethnic groups compared with others (Kurtz, Linnemann, and Spohn, 2008). In this framework, decisionmakers are influenced by emotions driven by the perception of minority youth as threatening to middle-class standards and public safety (Leiber and Fox, 2005). Reference is often made to the work of scholars such as Tittle and Curran (1988), who explored how negative perceptions of Black youth and stereotypes affect decisionmakers. A recent study expanded the definition of “threat” and found that higher rates of county-level homicide prosecutions and racial differences in unemployment were associated with secure detention and placement of youth (Fix et al., 2021). The authors concluded that racial threat and other theories aiming to explain racial disparities should be reexamined and modified to include markers of violent and sexual offenses.
Similarly, labeling theory posits that dominant groups maintain their status by using labels to define deviant or criminal behavior and disenfranchise certain other groups (Tapia, 2010). One example of labeling theory is when youths who experience police stops align their identities with the delinquent label and subsequently engage in illegal activities (McGlynn–Wright et al., 2020). For example, one recent study found that being stopped or arrested not only increased future delinquency but also amplified deviant attitudes (Wiley and Esbensen, 2016).
Other theories from the differential treatment framework include individual-level approaches such as attribution theory, which posits that decisionmakers may rely on internal and external factors they perceive to be linked to blameworthiness and delinquent behavior (Lowery and Burrow, 2019; Rodriguez, 2007:633), and focal concerns theory, which examines the factors that guide actors’ decisions in the justice system and the mechanisms by which these focal concerns shape final case outcomes (Harris, 2009).
In terms of attribution theory, researchers have demonstrated that juvenile justice decisionmakers are more likely to assign negative internal attributes (e.g., personality, attitude, cooperativeness) to youths of color and negative external attributes (e.g., delinquent peers, family conflict, school issues) to white juveniles; this is an important finding, for researchers have found that decisions are influenced more by negative internal attributes than by negative external attributes (Bridges and Steen, 1998; Beckman and Rodriguez, 2021). To empirically test the negative attributions theory, a recent study of diversion decisions found that youths of color were more likely to be linked to negative internal attributions in their files, in comparison with white youths, and that negative internal attributions in turn decreased the probability of receiving diversion (Beckman and Rodriguez, 2021). Another recent study examined the effects and intersections of race, legal characteristics, and macro-level community characteristics on juvenile institutionalization through the lens of attribution theory, concluding that race does influence confinement decisions (Lowery and Burrow, 2019).
Several studies have applied a focal-concerns framework to explain racial disparities in juvenile justice by examining the differences in the focal concerns of decisionmakers at different points of the system (Bishop, Leiber, and Johnson, 2010; Ericson and Eckberg, 2016). A key assertion of the focal concerns framework is that decisionmakers have limited time and information to make decisions, so they develop “perceptual shorthand,” which is often conditioned by stereotypes, extralegal factors, and legal cues (Hartley, Maddan, and Spohn 2007; Hawkins 1981; Ishoy and Dabney, 2018). The juvenile system consists of a several different independent bureaucracies that are responsible for decisions at different points of the process, and each set of bureaucracies contributes some outcome or information that pertains to the next point. Bishop, Leiber, and Johnson (2010) hypothesized that focal concerns would influence outcomes at loosely coupled points (intake, detention, disposition), but not at tightly coupled points (petition, adjudication), and found that their findings were generally consistent with these expectations.
Another explanation under the differential treatment framework is the liberation hypothesis (Guevara et al., 2011; Spohn and Cederblom, 1991). This hypothesis posits that in less-serious cases and when evidence is less conclusive, there is more ambiguity for decisionmakers, thus decisions are more likely to be influenced by race or other extralegal factors. In other words, the decisionmakers are “liberated” from legal constraints and therefore individualize the decision on a variety of factors, including racial and ethnic biases. Though limiting decisionmaker discretion using culturally competent, standardized decisionmaking tools is a main component of most approaches designed to reduce racial and ethnic disparities (e.g., Cabaniss et al., 2007; Center for Children’s Law and Policy, 2015; Hinton Hoytt et al., 2003; Nellis, 2005), some studies have failed to find support for the liberation hypothesis, which posits that this discretion is a contributing factor to disparities. In their study of juvenile court referrals in a northeastern state, Beaudry–Cyr and colleagues (2020) failed to find support for their hypothesis that extralegal factors would have a diminishing effect on case outcomes as the severity of the case increased. Similarly, in their study of factors that influence pre-adjudication and disposition outcomes between an urban and suburban county, Taylor and colleagues (2012) found there were more varying effects of legal and extralegal factors across race in the urban county than in the suburban county. Their interpretation of the liberation hypothesis was that there would be more of a due-process orientation in the urban locations, which would result in greater reliance on legal factors; their findings did not support this hypothesis.
Various scholars have identified shortcomings in looking exclusively at either the differential offending framework or the differential treatment framework (e.g., Tracy, 2005; Pope and Feyerherm, 1990; Bishop, 2005). With a complex social problem such as racial and ethnic disparity, numerous factors are likely at work, including poverty, segregation, educational challenges, residential instability, and the broader “racialized society” in which many institutional practices, public policies, and cultural representations operate (National Research Council, 2013). Thus, racial/ethnic disparities are “not reducible to either differential offending or differential selection” (National Research Council, 2013).
In addition to differential involvement and differential treatment, Engen and colleagues (2002) proposed two other perspectives: macro-contextual explanations and structural–processual explanations. Both mention that differential treatment may take place in some contexts but not in others (Zane and Pupo, 2021). The key issue for the structural–processual perspective is the separate and interrelated decisions of system processing, while the macro-contextual explanations focus on larger societal and community-levels factors (Rodriguez, 2007; Sampson and Wilson, 1995).
The current literature measuring the effectiveness of interventions to reduce racial and ethnic disparities generally involves comparing numbers, percentages, rates, or relative rates before and after the implementation of an intervention. Changes in disparities can happen at the local, state, or federal level. Thus, researchers must be clear on how and where changes in disparities are targeted and measured.
Several frameworks and strategies for reducing racial and ethnic disparities in juvenile justice have been developed, promoted, implemented, and evaluated. Leiber and Fix (2019) examined the effect of three of these large-scale initiatives: 1) the OJJDP requirement to address racial disparities in the JJDPA, 2) the Annie E. Casey Foundation’s Juvenile Detention Alternatives Initiative (JDAI) model (often implemented in partnership with the W. Haywood Burns Institute), and 3) the MacArthur Foundation's Models for Change initiative. Overall, the study found that these three efforts were often ineffective, though some practices had mixed support. They concluded that the common factors found to effectively reduce racial and ethnic disparities included
- Access to data collection and utilization.
- Stability in terms of employment for those receiving services.
- Collaboration among various agencies.
- Affiliation with other efforts to prevent delinquency and racial and ethnic disparities.
- System change (most notably in the form of developing and implementing racially and ethnically neutral objective decisionmaking tools).
- Cultural competence training.
- Commitment to disparity reduction in the short and long terms.
- State and local leadership.
- Long-term partnerships with universities and/or people trained in methodologies to aid in the study, implementation, and evaluation of strategies and interventions.
Before the Leiber and Fix study, an OJJDP–funded study identified nine jurisdictions that were able to decrease racial disparities as measured by the RRI and conducted case study research to describe the interventions that led to these reductions (Spinney et al., 2014). The researchers found that jurisdictions that successfully reduced disparities in their systems used nine primary strategies, several of which were identified by Leiber and Fix (above). In addition to the strategies identified by Leiber and Fix, the Spinney and colleagues (2014) case study research identified the following additional strategies: shifting the institutional culture from a punitive or procedural focus toward a focus on what was best for the youths and the community; creation of alternatives to secure detention, secure confinement, and formal system involvement; directing reduction interventions at the system (and not at the youths); and changing policies, procedures, and laws.
One example of a successful jurisdiction in the Spinney and colleagues (2014) study was Bernalillo County, NM, a jurisdiction that was able to decrease disproportionality (as measured by the RRI) in arrests, referrals to court, and diversions from the juvenile justice system for Black, Hispanic, and Native American youths. For example, in 2004, the arrest rate for Black youth was 16.4 per 100 youths while the white arrest rate was 8.8 per 100 youths, resulting in an RRI of 1.9. By 2010, the Black arrest rate had declined to 7.1, while the white arrest rate declined to 6.6, resulting in an RRI of 1.1. Bernalillo County’s sustained reductions in racial disparities at multiple stages of the juvenile justice system for Black, Hispanic, and Native American youths was likely a result of multiple strategies designed primarily around systems reform, attention to data, and increasing community-based services for court-involved youth. Strategies included implementation of the JDAI framework, emphasis on reducing the number of youths in secure detention, enhanced services for detained youths after returning to the community, establishment of a unit to increase access to diversion, and involvement of multiple partners over long periods of time in their efforts, even when individuals moved to new positions.
Several other publications describe reductions in racial and ethnic disparities (Hinton Hoytt et al., 2003; Nellis and Richardson, 2010; Shoenberg, 2012; Spinney et al., 2014). For example, a study of an intervention to reduce failures to appear in court in one jurisdiction was evaluated to identify whether there was a reduction in disparities as a result (Walker et al., 2019). The authors found that although the program significantly reduced the likelihood of youths failing to appear in court at the first court hearing following a summons (arraignment), it did not affect subsequent hearings and had no effect on reducing racial disparities. Another study that examined the use of a risk assessment instrument (RAI) in a midsized county in the Midwest found that the instrument did not eliminate racial and ethnic disparity in secure detention placements; however, that study suggested that the use of an RAI may reduce the effect of race on detention placement decisions (Mallett and Stoddard–Dare, 2010).
At least two evaluations examined the effect of multifaceted juvenile justice reforms at the state level. Donnelly (2019) examined changes in racial and ethnic disparities at secure detention and placement decisions in three Pennsylvania counties after the implementation of several juvenile justice reforms. Reforms included development of alternatives to secure detention and placement, revision of a RAI to inform detention proceedings, modification of the placement decisionmaking guidelines and process, and partnership with the Models for Change initiative. The author of the study found that the reforms resulted in a greater reliance on legal factors in decisionmaking, which should moderate the effect of race on processing outcomes.
Zane (2021) examined whether racial and ethnic disparities declined in Connecticut between 2000 and 2010, after the state had made substantial reforms, which included police training for working effectively with youth, development of a model memorandum of understanding for police officers and schools to use to reduce school-based arrests and referrals to court, funding for projects to build relationships between youth and police in local jurisdictions, and establishing two informational campaigns: Just.Start, which focused on addressing disparities in the juvenile justice system, and Right Response CT, which concentrated on schools and police knowing the “right response” to youth misbehavior. During this period, there was steady leadership from the Juvenile Justice Specialist, and the State Advisory Group later contributed to developing and executing these strategies (Spinney et al, 2014). Zane (2021) found that Black–white disparities in detention decreased over time. However, Black–white disparities increased for petition, adjudication, and waiver, and Hispanic–white disparities increased for adjudication (while not changing for other outcomes). Another analysis of changes in racial disparities in Connecticut found that during 2006–12 the RRI values at referral to court declined from 2.9 to 1.6 for Hispanic youth and from 6.3 to 4.7 for African American youth (Spinney et al., 2014).
Given the methodological challenges of evaluating comprehensive interventions to reduce racial and ethnic disparities, most of the more rigorous program evaluations examine the effect of specific, direct services to reduce differential offending among youths of color, which is just one of many plausible contributing factors.
A few programs are designed specifically for youths of color. For example, Protecting Strong African American Families (ProSAAF) is designed to improve family functioning and enhance youth development by targeting parents’ relationships and parenting skills. One study found that families who participated in ProSAAF saw statistically significant improvements in parental monitoring, self-concept, conduct problems, and substance-use initiation (Beach et al., 2016). Project Venture is a prevention program designed for at-risk Native American youths. This outdoor experiential program resulted in statistically significant reductions in the growth of substance use, including alcohol, marijuana, and other illicit substances (Carter, Straits, and Hall, 2007).
In addition to programs designed specifically for youths of color, mainstream programs can also result in positive outcomes. A meta-analysis of 350 studies of programs addressing juvenile delinquency found no evidence that mainstream delinquency intervention programs yield poorer outcomes for minority youth than for white youth (Wilson, Lipsey, and Soydan, 2003). Thus, targeting those interventions to youths of color may reduce disparities in a jurisdiction. Some examples of evidence-based intervention programs from the Model Programs Guide include the following:
The Child–Parent Center Program is a school- and family-based early intervention program that provides comprehensive educational and family support services to economically disadvantaged children. A longitudinal study that followed more than 1,500 predominantly Black children growing up in a high-poverty area of Chicago, IL, found that this intervention resulted in statistically significant declines in substance use, incarceration rates, and felony arrest rates at age 24 (Reynolds and Ou, 2011).
The Little Village Gang Violence Reduction Project is a comprehensive gang violence reduction program with five core elements: 1) community mobilization, 2) social intervention, 3) provision of social opportunities, 4) suppression, and 5) organization change and development of local agencies and groups. An evaluation of the project in the Little Village neighborhood of Chicago, which is predominantly Hispanic, found that the intervention resulted in statistically significant reductions in total violent crime, serious violent crime, and drug crime arrests (Spergel et al., 2003).
Project BUILD (Broader Urban Involvement and Leadership Development, now the BUILD Violence Intervention Curriculum), is a violence prevention curriculum designed to help youths in detention overcome problems they may face in their communities, such as gangs, drugs, and crime. The program is designed to intervene in the lives of youths who have come into contact with the juvenile justice system to reduce recidivism and diminish the prospects that they will become adult offenders. A 2000 study by Lurigio and colleagues found that youths who participated in Project BUILD had statistically significantly lower rates of recidivism, compared with nonparticipants.
However, these interventions do not address community-level and systems-level contributing factors to racial disparities, which many practitioners, policymakers, and advocates identify as the most important to address.
The existence of racial and ethnic disparities in the U.S. juvenile justice system is a complex issue. Its causes are multifaceted, and methodologically rigorous studies linking interventions to systemwide decreases in these disparities are not available (National Research Council, 2013:234–235). The evaluations that do exist find mixed results. Exacerbating the difficulty of addressing this issue is the fact that disparities exist well before contact with the juvenile justice system has occurred—in child welfare, the foster care system, school readiness, school performance, and school suspensions and expulsions (HHS, 2021; Knott and Giwa, 2012; Morris and Perry, 2016). Youths of color are more likely to live in single-parent families, in poverty, in disadvantaged communities with low performing schools, and in high-crime areas (Hirschfield, 2018; Moak et al., 2012; National Research Council, 2013). Given the problem’s extent and complexity, this issue is difficult to address.
The 2013 National Research Council report on reforming juvenile justice summarized the continued need to address this complex issue: 1) the existence of racial and ethnic disparities in the juvenile justice system raises questions of bias, fairness, and legitimacy regarding its functioning; and 2) these disparities raise questions about the larger life-course trajectories of many youths in minority communities who may become marked by criminal records early in life (2013:211).
Since 1988, OJJDP has mandated that states participating in the federal Title II Formula Grant Program address racial and ethnic disparities, and jurisdictions across the United States have made attempts to reduce these disparities. Although there is no conclusive evidence of what works to eliminate racial disparities, appropriate responses most likely require a multifaceted approach (Cabaniss et al., 2007; Center for Children’s Law and Policy, 2015; Donnelly, 2019; OJJDP, 2009b; Pope, Lovell, and Hsia, 2002; Spinney et al., 2014; Spinney et al., 2018).
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Suggested Reference: Development Services Group, Inc. 2022. "Racial and Ethnic Disparity (R/ED) in Juvenile Justice Processing." Literature review. Washington, DC: Office of Juvenile Justice and Delinquency Prevention. https://ojjdp.ojp.gov/model-programs-guide/literature-reviews/racial-and-ethnic-disparity
Prepared by Development Services Group, Inc., under Contract Number: 47QRAA20D002V.
Last Update: March 2022