Disproportionate minority contact (DMC) assessment [May 2012]

GOVERNOR'S OFFICE FOR CHILDREN AND FAMILIES
DISPROPORTIONATE MINORITY CONTACT (DMC) ASSESSMENT
MAY 2012
PREPARED BY THE
CONTACT: Matt Hauer Genevieve Vaida Governmental Services and Research Carl Vinson Institute of Government The University of Georgia

GOVERNOR'S OFFICE FOR CHILDREN AND FAMILIES
DMC ASSESSMENT MAY 2012
TABLE OF CONTENTS A. EXECUTIVE SUMMARY/INTRODUCTION .......................................................................................... 1 B. DMC LITERATURE REVIEW AND OVERVIEW OF DMC ....................................................................... 2 C. STATE & LOCAL DMC DELINQUENCY PREVENTION & SYSTEMS IMPROVEMENT STRATEGIES ........... 3 D. ASSESSMENT STUDY GOALS ............................................................................................................ 6 E. ASSESSMENT/STUDY FINDINGS ....................................................................................................... 9 F. CONCLUSIONS/RECOMMENDATIONS ............................................................................................ 12 TABLES AND MAPS............................................................................................................................. 16
Table 1. Statewide DMC Phase I Index Matrix, 2008-2010 .............................................................. 17 Table 2. Chatham County DMC Phase I Index Matrix, 2008-2010 .................................................... 18 Table 3. Clayton DMC Phase I Index Matrix, Jan-Dec 2008-2010 ..................................................... 19 Table 4. DeKalb DMC Phase I Index Matrix, Jan-Dec 2008-2010 ...................................................... 20 Table 5. Fulton DMC Phase I Index Matrix, Jan-Dec 2008-2010 ....................................................... 21 Table 6. Gwinnett DMC Phase I Index Matrix, Jan-Dec 2008-2010................................................... 22 Table 7. Newton DMC Phase I Index Matrix, Jan-Dec 2008-2010..................................................... 23 Table 8. Mobility Effects on RRI in Chatham County ....................................................................... 24 Table 9. Offense Status, Offense Type, Median Offense Rank, and RRI for Chatham County ........... 25 Table 10. Reduced RRIs based on Offense Data, for Black youth ..................................................... 26 Table 11. Data Availability.............................................................................................................. 27 Map 1. Black Referrals and Schools' Overall Percent with Free and Reduced Lunch and Black Enrollment ..................................................................................................................................... 28

GOVERNOR'S OFFICE FOR CHILDREN AND FAMILIES
DMC ASSESSMENT REPORT APRIL 2012
A. EXECUTIVE SUMMARY/INTRODUCTION Disproportionate minority contact (DMC) continues to be an issue facing the juvenile justice
system. While the number of delinquency cases for all race groups have increased since the passage of the Juvenile Justice and Delinquency Prevention Act of 1988 (JJDP Act), increases in the number of cases are larger for Black and other minority youth than for White youth. In 2000, delinquency case rates for Black youth were over twice the rate for White youth, and three times the rate for youth of other races.1 The discrepancy between these youths' interactions in the juvenile justice system shows the pervasive and subtle nature in which disproportionally continues to occur.
DMC at the state level occurs most acutely at sentencing to adult court, but at the county level disproportionality occurs most acutely at the referral stage. Six counties in Georgia currently have some of the highest DMC rates at referral: Chatham, Clayton, DeKalb, Fulton, Gwinnett, and Newton. The disproportionality in those counties is largely explainable through two contributing mechanisms: mobility effects and differential behavior. The lack of comprehensive data is prohibitive for deeper understanding of the nature and causes of this disproportionality, and conclusions about court policies or causality of these effects are unable to be made due to data inadequacy.
The current data system that exists for the Georgia juvenile justice system is inadequate for the robust study that DMC requires. Multiple layers of data collections, differing definitions of decision points, missing data, varying data quality across counties, and the lack of a cohesive and comprehensive juvenile justice data system are just a few of the problems that prohibit a more in-depth DMC study. The development and institution of new policies for the collection of better data are imperative for conducting a deeper, more robust DMC study in the future.
1 Cabaniss, Emily R., James M. Frabutt, Mary H. Kendrick, and Arbuckle, Margaret B. 2007. "Reducing Disproportionate Minority contact in the juvenile justice system: promising practices." Aggression and Violent Behavior, Volume 12, Issue 4, July-August 2007, 393-401.

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B. DMC LITERATURE REVIEW AND OVERVIEW OF DMC Beginning in 1988 the JJDP Act required states to examine disproportionate minority
confinement. The Act defined disproportionate minority confinement in broad terms "the proportion of juvenile minorities in confinement exceeds their proportion in the general population."2 Over the next decade, researchers would realize the importance of race at all decision points in the juvenile justice system.
In 2002, the JJDP Act broadened the states' examination requirements from confinement to contact.3 The change extended the focus from confinement alone to all decision points in the juvenile justice system. Today "racial differences that begin with juvenile involvement in crime become larger as youth make their way through different stages of the juvenile justice system from detention, to formal hearings, to adjudications, to out-of-home placements, and finally to waiver to adult court." 4 If youth continue to have disparate experiences throughout the justice system, the JJDP Act encourages states to be more comprehensive with intervention strategies and to recognize that disproportionate contact exists at stages other than detention or confinement.5
Early research that focused on confinement shows either mixed or no race effects within the juvenile justice system. Rather, the research shows age, prior record, geographic structural features, and procedural differences as the main causes of disproportionate confinement.6 Differential behavior, including type of offense, and severity of offense, is often considered one of the main reasons for disproportionate contact.7 For instance, Fagan and Deschenes' seminal study in 1990 focuses on factors leading to waivers to adult court. They found that "the relationship between race and transfer...hints broadly at racial discrimination".8 Still their research found that minority adolescents commit violent

2 The Juvenile Justice and Delinquency Prevention Act of 1974, Pub. L. no. 93-415, 42 U.S.C. 5601 et seq (1974).
Print. 3 Piquero, AR. 2008. "Disproportionate Minority Contact." The Future of Children, Vol.18, No. 2, 59. 4 Piquero, AR. 2008. "Disproportionate Minority Contact." The Future of Children, Vol.18, No. 2, 60. 5 US Department of Justice Office of Justice Programs. 2009. Disproportionate Minority Contact Technical Assistance Manual. 4th Edition, Chapter 1: Introduction, 1. 6 Fagan, Jeffrey. 1996. "The Comparative Advantage of Juvenile vs. Criminal Court Sanctions on Recidivism Among
Adolescent Felony Offenders." Law and Policy, Volume 18, Issue 1 and 2. 7 Fagan, Jeffrey. 1990. "Treatment and reintegration of violent juvenile offenders: Experimental results." Justice
Quarterly, 7, 233-263. 8 Fagan, Jeffery and Deschenes, Elizabeth P. 1990. "Determinants of judicial waiver decisions for violent juvenile
offenders." The Journal of Criminal Law and Criminology, Vol. 81, No. 2, 336.

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crimes at proportionally higher rates when compared to youth.9 The relationship between race and prior record has also been shown to skew the effects of race.10
Another avenue of research explains disproportionate minority contact as a result of differential treatment. 11 Piquero notes, "minorities are confined disproportionately for all offenses...the disproportion is greater when offenses are less serious, and discretion is typically built into decision making for such offenses."12 Policy implementation and legal factors have also been shown to heighten racial disparities. Research suggests that policies that target specific aspects of delinquent behavior, or a specific location, can disadvantage minority youth.13
Extralegal factors such as school, family background, or socio-economic status, have been found to have an effect on minority contact with the juvenile justice system.14 DeJong and Jackson's research on race in the juvenile justice system discovered that differential sentencing patterns between Black, Hispanic, and White juveniles are often correlated with family background (single mother household) and geographic location.15
Referred to as Justice by Geography, early research notes that geographic location of a court is important in determining decisions. DeJong and Jackson's research explains the importance of population density on decision-making. "Juveniles seem to be treated differentially according to court location. For White youths, court location does not affect the placement decision, whereas Black youths are more likely to be placed in counties with lower population density".16 Although population density negatively effects referral decisions, counties with a higher population density were found to have fewer placements of juveniles in a secure facility.17
C. STATE & LOCAL DMC DELINQUENCY PREVENTION & SYSTEMS IMPROVEMENT STRATEGIES There are three main sources of data for the DMC study. The first source is The Georgia Juvenile
Justice Data Clearinghouse (Clearinghouse), which is an aggregate data set for all 159 counties covering the years 2008 through 2010. The Clearinghouse aggregates across the number of youth in the following

9 Fagan, Jeffery and Deschenes, Elizabeth P. 1990. "Determinants of judicial waiver decisions for violent juvenile
offenders." The Journal of Criminal Law and Criminology, Vol. 81, No. 2, 336. 10 For more research on this topic see: Feld 1995, Sanborn 1996 11 For more research on this topic see: Leiber 1994, Bridges 1995, Wordes 1995, Bishop 1996 12 Piquero, AR. 2008. "Disproportionate Minority Contact." The Future of Children, Vol.18, No. 2, 60. 13 US Department of Justice Office of Justice Programs. 2009. Disproportionate Minority Contact Technical Assistance Manual. 4th Edition, Chapter 2: Assessment, 2-9. 14 For more research on this topic see: Sanborn 1996, DeJong and Jackson 1998, Sealock and Simpson 1998 15 DeJong, Christina and Jackson, Kenneth C. 1998. "Putting race into context: race, juvenile justice processing, and
urbanization." Justice Quarterly, Vol. 15, No. 3, 487. 16 DeJong and Jackson. 1998. P. 502. 17 DeJong and Jackson. 1998. P. 498.

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categories: arrested 18 , referred 19 , diverted 20 , secure detention 21 , petitioned 22 , adjudicated as delinquent23, committed24, confined25, and transferred to adult court26. Calculations for arrest are included for 142 of the total 159 counties.
Aggregate data is also available from the Georgia Department of Juvenile Justice (DJJ), in conjunction with the Governor's Office for Children and Families. The data set is for seven decision points covering the years 2008 and 2009; youth detention center (YDC) and regional youth detention center (RYDC) admissions are incomplete.
A third data set covering the years 2008 through 2010 is also available from DJJ and contains information on the six independent courts27 in Chatham County, Clayton County, DeKalb County, Fulton County, Gwinnett County, and Newton County. The data is disaggregated, at the individual level, and

18 Unique juvenile/offense entry date combinations where the youth was NOT in secure placement (Regional Youth
Detention Center (RYDC) or Youth Development Campus (YDC)) at the time of the entry. Arrest category may
represent referrals to law enforcement, juvenile court, or DJJ. The number of juvenile arrests represents number of
unique referrals. Each referral can represent more than one charge. 19 "Case" and "Referral" are treated as synonyms, defined as a unique juvenile / offense entry date combination.
Multiple charges for the same youth entered on the same date, regardless of the "offense date" will be counted as
one "case" or "referral". Referral category represents referral charges to juvenile court and DJJ. 20 Diversion category represents the total number of cases diverted. These cases are where, among all charges in
the case, the most serious outcome is a diversion. Diversions are informal adjustment, abeyance, diverted
complaint withheld, mediation, and nolle prosequi. 21 Any instances that are contiguous periods of time spent in RYDCs. "New" means that the instance started during
the reporting period. Transfers between RYDCs will NOT be counted as new episodes. 22 Cases where, among all charges in the case, the most serious outcome is something other than a dismissal or
diversion. 23 Petitioned cases resulting in a delinquent finding. The charge must be a misdemeanor or felony. Delinquent
category represents finding of delinquency in juvenile court. Multiple charges may be associated with a single
finding of delinquency. 24 Petitioned cases where, among all charges in the case, the most serious outcome is a commitment to DJJ. 25 Secure confinement category represents the total number of youth placed in a Long Term Youth Development
Campus (LTYDC) or a Short Term Program (STP). 26 Cases where, among all charges in the case, the most serious outcome is a superior court (adult) sentence. Cases
sentenced in the adult court category represent the total number of superior court sentences with a unique court
date. 27 The state of Georgia has a unique juvenile justice system comprised of independent courts and
dependent/shared courts. There are 17 independent courts within the state of Georgia; Chatham, Clayton, Cobb,
Columbia, Crawford, DeKalb, Dougherty, Floyd, Fulton, Glynn, Gordon, Gwinnett, Hall, Peach, Spalding, Troup, and
Whitfield. Independent courts operate at a local level and hear all cases involving allegations of deprivation of
children under the age of eighteen, or unruly conduct, delinquency, or traffic violations concerning children under
the age of seventeen found within its jurisdiction. Independent court counties interact with any juvenile at the
following decision points, arrest, referral, diversion, petition, delinquent findings, and transfer to adult courts. If a
youth is arrested or referred to the justice system in an independent court county, then the court handles all
stages until commitment. If a youth is committed, placement authority is often transferred to the Department of
Juvenile Justice.

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includes the following: juvenile identification number, date of birth, zip code of residence, gender, race, and county of referral.
When comparing indices for all minority youth across decision points at the state level, juveniles sentenced to adult court have the highest Relative Race Index (RRI), which compares rates of juvenile justice contact experienced by different race groups, at 3.79. In comparison to other minority youth, Black youth experience the highest rate of DMC at this decision point. Indices for Asian, Hispanic, and Other Race youth are all lower than for Black youth, which suggests that DMC is not occurring as acutely at the state level for those racial or ethnic groups as it is for Black youth. Table 1 shows state levels of DMC across all decision points from the Clearinghouse.
Table 2 shows the available data and RRIs for all decision points for Chatham County. Tables 3 through 7 show the available data for Clayton County, DeKalb County, Fulton County, Gwinnett County, and Newton County, respectively. RRIs for each decision point are given where sufficient data exists for calculation. For each table, data shown in white are aggregate data obtained from the Clearinghouse. Data shown in gray is the disaggregated individual level data obtained from DJJ.
As Table 2 demonstrates, the highest RRI is observed at referral decision points. The data on sentencing to adult court does not allow for an adequate RRI to be calculated since there are no data available for the petitioned data point, however, the referral RRIs are higher for Chatham County than for the statewide average. All six counties in this study follow the same trend showing that referrals demonstrate the highest RRIs. Two counties in particular, Fulton and DeKalb, show very high RRIs at the referral decision point, which will require more in-depth analysis.
Data across the three systems analyzed (data obtained from the Courts themselves, data obtained directly from GOCF, and data available from the DJJ Clearinghouse) is not harmonized, and thus the data from each database are not comparable to the others. As Table 2 shows, data at any one decision point can fluctuate widely between aggregated data and disaggregated data. Both aggregated and disaggregated data shows that referrals and arrests have the highest RRIs across the six counties being studied, which is in contrast to State data from the Clearinghouse, where the highest RRI is for juveniles sentenced to adult court. The lack of continuity between data sets can lead to widely disparate results.
The variation in these contact points may be correlated to a variety of issues. Incomplete data may help explain differences in contact points across data sets and between the state and counties. A lack of information sharing may also lead to the wide difference of results calculated for RRIs.

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D. ASSESSMENT STUDY GOALS The goal of this study is to identify variables that contribute to disproportionate minority
contact at the decision point with both the highest observed RRI and the most stable data for Chatham, Clayton, DeKalb, Fulton, Gwinnett, and Newton counties for the years 2008-2010. The applicable decision point is referrals. At least two contributing mechanisms of DMC at this decision point are identified within these municipalities.
This study revolves around a detailed analysis of quantitative data obtained from DJJ. These data, as stated above, are disaggregated and contain several key variables for each individual youth who makes contact with the juvenile justice system. All data are processed using SAS 9.1. The contributing mechanisms of DMC are identified through this quantitative analysis, specifically by re-aggregating the data to identify anomalies and through the use of Chi-squares test of significance.
The lack of available data limits the depth and type of analysis that can be completed. The data are at the individual level, containing unique IDs for each youth, and for each contact a youth has with the justice system. In addition, the data contains race, gender, residential zip code, jurisdiction where contact with the justice department occurred, offense status, offense type, offense severity, and decision point for each youth. The referral decision point is analyzed because of the comprehensiveness of referral data, the lack of disaggregated data at other decision points, and the observed RRIs at this decision point. If better data was available, further analysis of each decision point would have been undertaken.
The geographic position of these six counties within the state lends itself to a deeper analysis of mobility effects. Specifically, five of the six counties are located in the Atlanta metro area, which has been characterized by high migration and attraction (malls, events, or entertainment facilities) for the last twenty years. The sixth county, Chatham, is likewise characterized by high migration and attraction and is home to the City of Savannah. It is hypothesized that the level of DMC observed in these jurisdictions is at least partially explained by youth from other areas entering these jurisdictions and committing crimes. This is potentially a tertiary effect that would throw off statistical analyses if not controlled for.
For the five counties in the metro Atlanta area, these mobility effects, youth from one spending time in another, really demonstrate that juvenile justice in the Atlanta area should be approached from a regional perspective, something independent courts would not be able to do, but DJJ could.
Furthermore, analysis of the referral decision point lends itself to a deeper understanding of schools' role in this decision point. These data have been mapped based on the zip code where the

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youth resides along with the high schools in each school district, the percentage of students on free and reduced lunch, and the percentage of enrollment for each minority group (See Map 1).
Additionally, data is thorough in relation to offense type28, severity29, and status30, allowing for an in-depth analysis of these three variables at the referral stage. This analysis should uncover anomalies between race groups in the justice system. These anomalies may be very specific to each county or could be an overarching anomaly for all the counties studied. It is hypothesized that minority youth are arrested at higher rates than White youth for similar crimes, despite offense severity being either on par or less severe, and that referrals are occurring in areas with schools characterized by large minority enrollment and free and reduced lunch enrollment.
The first analysis conducted is an analysis of mobility effects. The RRI is calculated in a two-step process. RRI is calculated twice, in two different ways, so as to observe mobility effects. The first, "Youth Within This County" calculates RRI by taking the number of crimes committed within a county and dividing by the juvenile population, those aged 0-17 years old, within the county. The second calculation of RRI, "Youth From This County", takes the number of crimes committed by youth from a particular county, no matter where the crime occurs, and divides by the total population of youth aged 0-17 years within the county. The difference in these two RRI calculations shows variability in RRI based on the mobility of youth of differing race or ethnicity.
The two RRIs demonstrate the count of actual crimes committed by the population from the jurisdiction, regardless of where contact with the juvenile justice system occurs, as well as the "normal" way of calculating RRI, by counting all of the contacts within a jurisdiction. Table 8 shows the results of this analysis for Chatham County.
The column "All Crimes' under the heading "Youth Within This County" is the total number of crimes committed by a particular race group recorded in Chatham County between 2008 and 2010 regardless of the youth's residence. The column adjacent is the total number of crimes committed by a particular race group residing in Chatham between 2008 and 2010. The difference in the number of crimes is the total number of crimes committed by youth who are reside in a county that is not Chatham County.

28 Offensive type has eleven categories: drug selling, drug use, property, public order, traffic, status, violent, violent
sex, sex non-violent, violation of parole, and weapons violation. Offensive type describes the crime category. 29 Severity for a crime is a numeric rank from 1 to 71, where the lower the number the more severe the crime is.
Murder is rank 1 while violation of probation is rank 71. 30 Crimes are also classified by status. Categories are felony, misdemeanor, or status. Violent crimes are most
often felonies or misdemeanors, while less serious crimes, such as probation violation are often status offenses.

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The column "All Crimes" under the heading "Youth From this County" is the total number of crimes committed by a particular race group by youth who resided in Chatham County between 2008 and 2010 regardless of where the crime is committed. The column adjacent is again the total number of crimes committed by a particular race group residing in Chatham between 2008 and 2010. The difference in the number of crimes between these two columns is the total number of crimes committed by youth in their home county and crimes the youth are committing outside of their county.
The "Percent Explanation" in RRI represents the difference between calculating RRI based on all crimes that are committed in Chatham County versus calculating RRI based only on youth who are from the county. When only counting youth who are committing crimes in Chatham County and who reside in Chatham County, there is a 25% explanation in RRI. Thus 25% of the RRI that is observed in Chatham County for Black youth is explainable through mobility effects.
Table 8 can also be interpreted as the number of crimes youth will commit in their home county versus crimes they will commit in other counties. Black youth who reside in Chatham County are more likely to commit crimes within their county of residence (2138 crimes in Chatham, 2368 crimes from Chatham regardless of county) when compared to White youth (243 crimes in Chatham, 420 crimes from Chatham regardless of county). Thus, White youth from Chatham County tend to travel outside of their county of residence when committing crimes while Black youth are more likely to commit crimes in their county of residence. This pattern repeats itself for the other five counties in this study.
Data is broken down further by offense status, offense type, and offense rank, allowing researchers to look at the differences in referral rates for crime types by race. It also can show the difference of the average severity for crimes being committed.
Table 9 shows the data for Chatham County. "Offense Rank" is on a scale of 1 to 71, with "1" considered most severe and "71" being the least severe. Different crimes may be ranked at the same severity level. For instance, voluntary manslaughter and feticide are both ranked as "2", although the crimes differ. As the rank lowers, closer to 71, more crimes share the same rank. For instance, 22 different crimes share the 71st rank. This disaggregated data allows researchers to create a tailored approach for each county and identify anomalies in the data. For instance, many of the offense categories across counties that are assigned to defendants have minimal differences between White and Black in terms of severity of the crimes. But in a few isolated instances, the severity of crimes for either Black or White is considerably different.
The researchers not only identify differences in the severity of the crimes, but also identify differences in the RRIs for the crimes, regardless of severity. Felony drug use in Chatham County is an

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example of an anomalous RRI for Black youth. Even though the `normal' RRI for Black youth is 5.21, the RRI for this crime group is 30.5.
Moving down the serious scale (felony->misdemeanor->status) in Table 9, for example, the RRI between Black and White youth gets reduced all the way to the point where no Black youth were referred for drug use. This indicates differential treatment for Black youth when compared to White, but the exact extent of this is unknown due to a lack of data on other decision points.
E. ASSESSMENT/STUDY FINDINGS MOBILITY EFFECTS Mobility effects show a clear explanation for a large part of the observed RRIs in these six
counties. Gwinnett was the only county for which mobility effects did not account for a large portion of its observed RRIs. This could be because Gwinnett does not have the same attractions for youth that many of the other counties have. See Table 10.
We would expect most crimes that are committed in a jurisdiction to be committed by youth residing in that jurisdiction, however, upward of one-third of the RRI is explained through mobility effects, and this is a rather large effect. Normal RRI calculations dictate the use of all crimes committed in a particular county, divided by the youth population in a particular county. However, calculating RRI this way is misleading. Dividing crimes committed in a particular county, regardless of where the youth are from, by the number of youth in that particular county inflates RRI. If instead RRI is calculated by looking at the number of crimes committed by youth from a particular county, regardless of the location of the crime, RRI is reduced and explained in a more meaningful way.
The data points to White youth leaving their county to commit a majority of crimes, whereas minority youth tend to commit a greater proportion of crimes within the counties they reside. When looking at the total number of crimes committed by a particular race, compared to the crimes these youth committed in their home county, 23% of all Black youth from the six counties committed crimes outside their home county compared with 40% of all White youth crimes. This distinct difference between White and Black youth leads to an inflated RRI for Black youth in these counties.
For instance, in Fulton County the RRI for all crimes committed in the county, regardless of where the youth is from, RRI is 24.2. However, if RRI is calculated by looking at all youth in the county who commit crime, regardless of where the crime is committed, RRI is reduced to 17.08. Although this RRI is still significantly higher than the other RRIs from the other five counties, the reduction shows that mobility effects helps explain why African American youth are being arrested at a higher rate than their White counterparts. Looking at the raw numbers it is evident that White youth from Fulton County

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commit more crimes outside of the county than within. African American youth also commit more crimes outside of Fulton County, but the increase is proportionally greater for White youth than for Black youth. The increase is 60% for Whites, as opposed to a 23% increase for African American youth.
This pattern is true for all six of counties analyzed. The effect is greatest for Fulton and DeKalb Counties, while it has the least effect on Gwinnett County. With the exception of Gwinnett County, this pattern was true for not just African American youth, but all minority youth. This indicates that mobility effects are a significant contributing mechanism to DMC in these six counties. More than likely, what is causing the pronounced mobility effects in Fulton and DeKalb Counties is the presence of attractive nuisances. For example, there are malls and shopping facilities that draw youth from across the region. In order to pinpoint these attractive nuisances, location data of the arrest or referral would be needed.
Furthermore, understanding mobility effects of youth within a given county will rely on subcounty census data. The Census Bureau is scheduled to release 2010 census zip code data in 2013. When that data is released, intra-county mobility effects can be studied in greater detail by further analyzing the demographic characteristics of youth and by coupling location of the youth and location of the crimes.
Map 1 shows the number of Black referrals by zip code, high schools, and the percentage of students on free and reduced lunch for all six counties in this study. The high schools are scaled based on the percentage of block enrollment (larger the circle, the higher the percentage) and are colored based on the percentage of all students enrolled in free and reduced lunch (the lighter the color, the higher the percentage).

The pattern of youth referrals is clear: areas with schools with both higher black enrollment and free and reduced lunch enrollment see higher referral rates for their black youth. Conversely, areas with high black enrollment but low free and reduced lunch enrollment do not show these high referral rates.
OFFENSE EFFECTS Chatham. Earlier in the analysis section, the researchers began discussing the effects of offense
status, type, and severity. Chatham County has five categories of crimes that are disproportionately greater for Black youth than for White youth. These are felony drug use, felony violent offense, misdemeanor sex (non-violent), misdemeanor weapons violations, and violation of parole. Felony drug use for Black youth is, on average, slightly less severe than for White youth, yet Black youth are referred at 31 times the White referral rate. Violent felony offenses are, on average, slightly less severe than for White youth, yet Black youth are arrested at 10 times the White arrest rate. Misdemeanor sex (non-

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violent) offenses are, on average, just as severe as White youth, but are arrested at nearly 43 times the White arrest rate.
Misdemeanor weapons violations are, on average, slightly less severe than White youth but are arrested at 9 times the arrest rate. Lastly, violation of parole for Black youth is 15 times higher than for White youth. It should be noted that White youth were arrested for status level drug use charges, but no Black youth were in this time period. These five crime groups account for over 500 contacts with the juvenile justice system out of 2400 contacts and account for 11% of the RRI. This evidence suggests that when intake occurs for these youth, some criminal behavior leads to different charges despite minority groups' less severe crimes.
DeKalb. DeKalb County has five categories of crimes that are disproportionately greater for Black youth than for White youth. These are felony drug selling, felony violent, misdemeanor public order, misdemeanor sex non-violent, and misdemeanor violent.
Crimes for felony drug selling are, on average, considerably less severe than for White youth, yet Black youth are arrested at nearly 14 times the White arrest rate. Felony violent crimes are, on average, slightly less severe than White youth, yet Black youth are arrested at 28 times the arrest rate of White youth. Crimes of misdemeanor public order are, on average, less severe than for White youth, yet Black youth are arrested at 16 times the White arrest rate. Crimes of misdemeanor sex non-violent are, on average, equally severe as White youth but Black youth are arrested at nearly 14 times the White arrest rate. And crimes of misdemeanor violent are, on average, equally severe as White youth but Black youth are arrested at 19 times the arrest rate. These five crime groups account for 15% of the RRI. When intake occurs for these youth, the same criminal behavior leads to different charges despite minority groups' less severe crimes.
Fulton. Fulton County has a number of crime groups that are disproportionately greater for Black youth than for White youth. These are felony property, felony public order, felony and misdemeanor violent, felony violent sex, felony weapons violations, misdemeanor sex non-violent, and misdemeanor and status violation of parole. These crimes have RRIs that range from 13.2 to 41.5. Most of these crimes are either just as severe as their White counterparts or are actually slightly less severe. These crime groups account for 31% of the RRI. Because the crimes are equally severe, this indicates differential offending as a contributing mechanism.
Gwinnett and Newton. Gwinnett and Newton's RRIs aren't as large as most of the other counties, but both still have a number of crime groups that are disproportionately greater. Felony public order and felony violent show the highest RRIs in Gwinnett. The other crime categories are felony property, misdemeanor public order, and misdemeanor and status violation of parole. However, these

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crime groups account for 16.5% and 19% of the RRI in these counties. This, too, indicates differential offending as a contributing mechanism.
General. In general, offense type correlates to RRI levels in each of the six counties being studied. Evidence shows that minority youth, in terms of count or number, have higher rates for these crimes indicating differential offending. However, the median offense rank of crimes (severity) is less for minority youth than for White youth. Felony Drug Use in Chatham County is one such example.
Data also indicates that Black youth who are referred for drug use are charged with a felony while White youth are more likely charged with a misdemeanor or status offense. This may indicate structural or policy issues. Current data is too limited to speculate what these structural or policy issues are exactly.
There are several crime categories where counts are higher for minority youth than for White youth. Differential offending occurs most among the following categories: violation of parole, violent crime, public order, non-violent sex offense, and property crime. The differences in the RRIs for the crimes, regardless of severity, shows evidence of differential offending as a contributing mechanism to DMC. Felony drug use in Chatham County is an example of an anomalous RRI for Black youth. Even though the `normal' RRI for Black youth is 5.21, the RRI for this crime group is 30.5. When felony drug use is removed from the RRI calculation RRI indexes are reduced, displaying differential offending patterns.
These crimes of differential offending all exhibit varying differences in disproportionate contact, but are overwhelmingly found as being disproportionate in the majority of the six counties. This shows that specific crimes, regardless of severity, have higher referral rates for Black youth than for White youth. These results indicate that similar crimes are being treated differently at the referral decision point; similar criminal behavior could lead to more serious charges (i.e., felony instead of status). The exact extent of this differential treatment is unknown without more in-depth DMC data for additional decision points.
All six counties in this study showed statistical significance at the 0.001 level for Black youth at the referral decision point. This decision point was the most statistically significant difference and indicates that policies tailored to the referral decision point should be undertaken.
F. CONCLUSIONS/RECOMMENDATIONS Limited data makes it difficult to make recommendations with confidence. However, there are a
number of policy implications from the current research on referral data.

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1) Programs directed at crimes that have been found to have differential offending patterns might be advantageous in helping youth. Direct Services would allow youth better access to prevention and early intervention programs so that the reception of services needed to build skills, improve social functioning, and form healthy relationships exists. While it is difficult to assess the cause of differential offending, prevention and early intervention programs might help lower this discrepancy.
2) Data review can be critical in reducing DMC across Georgia. It has been shown that by mapping data for each decision point, agencies can assess where the system may be disadvantaging minority youth.31 While decision-point mapping can be critical in reducing DMC and eliminating biased practices within agencies, other programs can be helpful in reduction. For instance, cultural competency training can be used within a police force to heighten awareness about DMC and underscore the importance of eliminating unnecessary juvenile arrests and referrals32. Sensitivity training may also help front line interactions with youth and reduce differential offending patterns.
3) Furthermore, the availability of adequate data to provide a robust DMC analysis is severely lacking. The presence of multiple datasets on the same data and the incongruity between agencies who collect this data create a data environment that is both incomplete and overtly complicated. Implementing a policy of more complete and harmonized data across systems would greatly improve any DMC analysis and go a long way to helping reduce DMC within Georgia. Simply having harmonized data that includes all decision points at a disaggregated level would be a huge boon for future DMC analyses.
4) Before full implementation of any sort of programs or comprehensive changes, it is important that future studies have complete data sets that allow for a real picture of what is occurring in the juvenile justice system in Georgia. In order to better understand what is occurring at all contact points, it would be helpful to have more extra-legal variables such as income and socio-economic status. The Census should be releasing zip code data in 2013 that can approximate socio-economic status. These data could be very helpful in understanding DMC. The lack of extra-legal variables eliminates the ability to test for

31 Cabaniss, Emily R., James M. Frabutt, Mary H. Kendrick, and Arbuckle, Margaret B. 2007. "Reducing
Disproportionate Minority contact in the juvenile justice system: promising practices." Aggression and Violent
Behavior, Volume 12, Issue 4, July-August 2007, 393-401. 32 Hoytt, E. H., Schiraldi, V., Smith, B. V., & Ziedenberg, J. 2002. "Pathways to juvenile detention reform: Reducing
racial disparities in juvenile detention." Pathways to Juvenile Detention Reform Series, Vol. 8.

DMC Assessment Report April 2012

14

contributing mechanisms not controlled or influenced by the DJJ the court system. Currently, a zip code in the independent court data set approximates residence for each youth, and a county number locates what court the youth was processed in. However, data that better pinpoints where youth are committing crimes might help to further flush out mobility effects. Also, the court system currently labels contact points as follows: referral, diversion, Youth Detention Center (YDC) and Regional Youth Detention Center (RYDC) admissions, petitions, delinquency findings, commitment to the Department of Juvenile Justice, and superior court sentencing. The contact points do not match either DJJ's or Clearinghouse's data sets. The discrepancy mostly lies within the RYDC and YDC contact points. In the clearinghouse data, these are specified as juveniles in secure detention or juveniles in confinement; in the DJJ aggregate data set these contact points are missing entirely. Defining these decision points across data sets can help make data comparable. The lack of arrest, diversion, petition, and adjudication decision points means that adequate RRIs cannot be calculated beyond the referral decision point. The lack of data cohesion across these three sets, or even between the Clearinghouse and the court system, is problematic if Georgia is to create a comprehensive and cohesive picture of DMC. A harmonized data system, with both aggregate and individualized data, would allow for research of court, state, and police policy that could provide a finer scale. GOCF has recently been working to improve data quality and this work must continue. Furthermore, an examination of individual court policies would also improve a DMC analysis. The inclusion of diversion, petition, and detention decision points alone would allow for an examination of these individual court policies. The overarching need to address DMC will require an improvement in data quality and collections, specifically data that is harmonized across all groups. The analysis of mobility effects in this study indicates the levels of mobility that youth have in traversing court systems. Youth processed in the courts later come under DJJ custody. They are pooling resources while not pooling data. This leads to incredible holes within the data that make a DMC analysis inaccurate. Rectifying this data through a policy of improved data relations would be immensely beneficial to a future DMC study. Table 11 shows the data availability between systems. Zeros in a cell indicate a lack of data. As you can see, there are no comprehensive data that includes all decision points in a single database. All DMC analyses on these six counties would require an incomplete decision point analysis or require combining incompatible data.

DMC Assessment Report April 2012

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Having an improved data system would allow for a considerably better DMC analysis. Implementing policies of better data acquisition and processing, or even agreements between the courts and DJJ for better data, would make a DMC study more robust.
Overwhelmingly, referral is the decision point with the highest DMC for these six counties. Very little DMC is occurring at the other seven decision points. But again, this is very hard to truly know since only Newton County has complete data for all decision points. Due to the very high observed RRIs at the referral decision point, future efforts should focus on referrals.

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TABLES AND MAPS (Remainder of Page Left Intentionally Blank)

DMC Assessment Report April 2012

17

Table 1. Statewide DMC Phase I Index Matrix, 2008-2010

Total Youth

1. Population at

Risk (Midpoint 2,442,690

2009)

2. Juvenile arrested 104,210

3. Juveniles Referred

174,503

Sum of Arrest and Referral

278,713

4. Juveniles

Diverted (denominator is

89,013

referral and arrest)

5. Juveniles in Secure Detention

58,922

6. Juveniles Petitioned

88,578

7. Juveniles result

in Delinquent

57,438

Findings

8. Juveniles Committed to DJJ

10,983

9. Juveniles in Confinement

11,658

10. Juveniles

sentenced to Adult

498

Court

*

<0.05

** <0.01

*** <0.001

White
1,241,238 43,958 58,125 102,083
33,213
13,921 26,342 17,135 2,156 2,787
50

Black or AfricanAmerican 802,133 54,367 101,243 155,610
48,992
39,757 53,785
35,325
7,771 7,917
410

Hispanic or Latino
312,975 4,223 11,675 15,898
4,998
4,120 6,742 4,002 831 752
30

Asian
79,559 170 822 992
465
178 373 221 50 34
1

Other /
Mixed
NA

Index for AA
0.80 1.13
-
0.97
1.87 1.38 1.01 1.75 0.79 4.02

Index for Hispanic
0.02 0.02
-
0.97
1.90 1.70 0.91 1.65 0.70 2.34

Index for
Asian

Chi Squared Significance,
AA youth

0.060

***

0.221

-

1.441

1.316

**

1.011

0.911

1.798 0.526

1.412

DMC Assessment Report April 2012

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Table 2. Chatham County DMC Phase I Index Matrix, 2008-2010

White

1. Population at Risk 2. Juvenile arrested Arrest Data not available 3. Juveniles Referred
Referrals 4. Juveniles Diverted
Diversions

5. Juveniles in Secure Detention

RYDC Admissions 6. Juveniles Petitioned
Petitions 7. Juveniles result in Delinquent
Findings Delinquency Findings 8. Juveniles Committed to DJJ
Commitment 9. Juveniles in Confinement
YDC Admissions

10. Juveniles sentenced to Adult Court

Superior Court Sentencing

*

<0.05

** <0.01

*** <0.001

25550 ---
1328 378 552 --
402
419 776 --
576
-47 47 66 42
1
1

Black/ AfricanAmerican
27352 ---
7212 2792 2144
--
3640
3446 5068
--
4017
-521 521 682 423
10
10

Hispanic/ Latino

Asian

Index AA

Index for H

Index for A

Chi Squares significance,
AA youth

3017

1304

--

--

--

--

117

14

5.07 0.75 0.21

***

32

2

6.90 0.72 0.10

***

53

8

0.72 1.09 1.37

***

--

--

--

--

--

***

25

2

1.67 0.71 0.47

31

2

1.11 0.87 0.90

64

6

1.20 0.94 0.73

--

--

--

--

--

46

5

1.07 0.97 1.12

--

--

--

--

--

3

0

1.59 0.80

0

3

0

3

0

0.93 0.93

0

3

0

0.91 1.12

0

0

0

1.5

0

0

0

0

DMC Assessment Report April 2012

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Table 3. Clayton DMC Phase I Index Matrix, Jan-Dec 2008-2010

Total Youth

White

Black/ AfricanAmerican

Hispanic/ Latino

Asian

Index Index AA for H

Index for A

Chi Squares significance,
AA youth

1. Population at Risk

78276 7274 52811

14207 3686

2. Juvenile arrested

--

--

--

--

--

Arrest Data not available

--

--

--

--

--

3. Juveniles Referred

8698 1328

7212

117

14 0.7 0.05 0.02

***

Referrals

2643 130

2328

172

13

2.5 0.7

0.20

4. Juveniles Diverted

2766 552

2144

53

8

0.7 1.09 1.37

Diversions

--

--

--

--

--

--

--

--

5. Juveniles in Secure Detention

4095 402

3640

25

2

1.7 0.71 0.472

RYDC Admissions

2054 95

1808

143

8

1.1 1.1

0.84

6. Juveniles Petitioned

5932 776

5068

64

6

1.2 0.94 0.73

Petitions

--

--

--

--

--

--

--

--

7. Juveniles result in Delinquent Findings

4658 576

4017

46

5 1.068 0.968 1.12269

Delinquency Findings

--

--

--

--

--

--

--

--

8. Juveniles Committed to DJJ

572

47

521

3

0

1.6 0.8

0

Commitment

518

23

466

29

0

**

9. Juveniles in Confinement 756

66

682

3

0

0.9 0.93

0

YDC Admissions

203

12

180

10. Juveniles sentenced to Adult Court

11

1

10

Superior Court Sentencing

21

2

19

*

<0.05

** <0.01

*** <0.001

10

1

0.7 0.66

0

0

0

1.5 0.0

0

0

0

DMC Assessment Report April 2012

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Table 4. DeKalb DMC Phase I Index Matrix, Jan-Dec 2008-2010

Total Youth

White

Black/ AfricanAmerican

Hispanic/ Latino

Asian

Index AA

Index for H

Index for A

Chi Squares significance,
AA youth

1. Population at Risk 2. Juvenile arrested Arrest Data not available 3. Juveniles Referred
Referrals 4. Juveniles Diverted
Diversions

169876 ----
4498 ---

39187 ---102 ---

96199 ----
4142 ---

25762 8226

--

--

--

--

--

--

--

--

--

--

--

--

234

20 16.5 3.5 0.9

--

--

--

--

--

--

--

--

--

--

5. Juveniles in Secure Detention 4830 119

4373

275

22

--

--

--

RYDC Admissions

4680 108

6. Juveniles Petitioned

--

--

Petitions

--

--

7. Juveniles result in Delinquent Findings

--

--

Delinquency Findings

--

--

8. Juveniles Committed to DJJ

875

7

Commitment

875

7

9. Juveniles in Confinement

435

5

YDC Admissions

314

1

10. Juveniles sentenced to Adult Court

51

0

Superior Court Sentencing

50

0

*

<0.05

** <0.01

*** <0.001

4305 ---
--
-811 811 392 290
47
47

249

18 1.0 1.0 0.9

--

--

--

--

--

--

--

--

--

--

--

--

--

--

--

--

--

--

42

9

42

9

31

3

0.7 0.7 0.5

21

2

2.5 3.5 1.6

2

1

2

1

DMC Assessment Report April 2012

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Table 5. Fulton DMC Phase I Index Matrix, Jan-Dec 2008-2010

Total Youth

White

Black/ AfricanAmerican

Hispanic / Latino

Asian

Index AA

Index Index for H for A

Chi Squares significance,
AA youth

1. Population at Risk

235975

85445

108256

31032

1124 2

2. Juvenile arrested

0

--

--

--

--

Arrest Data not available

0

3. Juveniles Referred

16365

1265

14345

701

54

9.0

1.5 0.32

***

Referrals

6652

197

6253

178

24

25.1

2.5

0.9

4. Juveniles Diverted

7220

825

6046

325

24

0.6

0.7 0.68

Diversions

0

--

--

--

--

--

--

--

5. Juveniles in Secure Detention

6788

189

6418

166

15

3.0

1.6 1.86

RYDC Admissions

6038

171

5714

139

14

1.1

0.9 0.67

6. Juveniles Petitioned

9145

440

8299

376

30

1.7

1.5 1.60

Petitions

0

--

--

--

--

--

--

--

7. Juveniles result in Delinquent

2837

120

2597

111

9

1.1

1.1 1.10

Findings

Delinquency Findings

0

--

--

--

--

--

--

--

8. Juveniles Committed to DJJ

779

10

745

16

8

3.4

1.7 10.7

***

Commitment

779

10

745

16

8

9. Juveniles in Confinement

199

2

189

8

0

1.3

1.3 0.0

YDC Admissions

197

1

186

7

3

2.5

4.4 3.8

10. Juveniles

sentenced to Adult

68

Court

0

66

2

0

0.0

0.0 0.0

Superior Court Sentencing

68

0

66

2

0

*

<0.05

** <0.01

*** <0.001

DMC Assessment Report April 2012

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Table 6. Gwinnett DMC Phase I Index Matrix, Jan-Dec 2008-2010

Total Youth

White

Black/ AfricanAmerican

Hispanic / Latino

Asian

Index AA

Index for H

Index for A

Chi Squares significance,
AA youth

1. Population at Risk

231399 93426 55783

58561 22810

2. Juvenile arrested

--

--

--

--

--

Arrest Data not available

--

--

--

--

--

--

--

--

3. Juveniles Referred

13995 4021

6125

3065

418 2.6 1.2 0.4

***

Referrals

3139 745

1509

829

56

3.4

1.8

0.3

4. Juveniles Diverted

5256 1611

2248

1046

206 0.9 0.9 1.23

Diversions

--

--

--

--

--

--

--

--

5. Juveniles in Secure Detention

2884 617

1354

748

51

1.4

1.6

0.8

RYDC Admissions

2714 617

1310

734

53

1.0

1.1

1.1

6. Juveniles Petitioned

8739 2410

3877

2019

212 1.1 1.1 0.85

Petitions

--

--

--

--

--

--

--

--

7. Juveniles result in Delinquent Findings

5294 1539

2313

1183

128 0.9 0.9 0.95

*

Delinquency Findings

--

--

--

--

--

--

--

--

8. Juveniles Committed to DJJ 1203 268

549

334

19

1.4

1.6

0.9

***

Commitment

1170 268

549

334

19

9. Juveniles in Confinement 574

91

261

177

17

1.4 1.40 2.64

***

YDC Admissions

337

56

162

10. Juveniles sentenced to Adult Court

12

0

10

Superior Court Sentencing

12

0

10

*

<0.05

** <0.01

*** <0.001

110

9

1.4 1.6 2.27

2

0

0

0

0

*

2

0

DMC Assessment Report April 2012

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Table 7. Newton DMC Phase I Index Matrix, Jan-Dec 2008-2010

1. Population at Risk 2. Juvenile arrested Arrest Data not available 3. Juveniles Referred
Referrals Sum of Referral and Arrest
4. Juveniles Diverted Diversions

5. Juveniles in Secure Detention

RYDC Admissions

6. Juveniles Petitioned

Petitions

7. Juveniles result in Delinquent Findings

Delinquency Findings

8. Juveniles Committed to DJJ

Commitment

9. Juveniles in Confinement

YDC Admissions

10. Juveniles sentenced to Adult

Court

Superior Court Sentencing

*

<0.05

** <0.01

*** <0.001

Total Youth
27696 996 -1105 1105 2101 176
507
940 924 836 821 105 103 137
9 9

White
14167 254 -282 282 536 50 50
131
125 244 244
215
215 26 26 36 35
1
1

Black/ AfricanAmerica
n
11631 691 -767 767 1458 120 120

Hispanic / Latino
1539 37 -38 38 75 4 4

Index AA
3.31 --
3.31 3.31
-0.88 0.88

Index for H
1.34 --
1.24 1.24
-0.57 0.59

Chi Squares significance,
AA youth
***
***

358

14

1.00 0.22

318

11

0.94 0.83

646

34

0.97 1.00

646

34

0.97 1.03

578

28

1.02 0.93

578

28

1.02 0.93

75

2

1.07 0.59

75

2

1.07 0.59

99

1

0.95 0.36

73

1

0.72 0.37

8

0

3.0

0

8

0

3.0

0

DMC Assessment Report April 2012

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Table 8. Mobility Effects on RRI in Chatham County

Youth Within This County

Youth From this County

All Crimes

All Crimes Inside Their
County

RRI

All Crimes

All Crimes Inside Their
County

Percentage

RRI

Explanation

in RRI

White

371

243

420

243

Black

2769

2138

6.90

2368

2138

5.21

24.5%

Am. Indian

1

1

0.34

1

1

0.30

11.7%

Asian

2

0

0.11

1

0

0.05

55.8%

Hispanic

32

13

0.74

24

13

0.49

33.8%

DMC Assessment Report April 2012

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Table 9. Offense Status, Offense Type, Median Offense Rank, and RRI for Chatham County

Offense Status
F F F F F F F F
F
M M M M
M
M M M M
M
S S S

Offense Type
DRUG SELLING DRUG USE PROPERTY
PUBLIC ORDER TRAFFIC VIOLENT
VIOLENT SEX VOP/VOAC/VOAP
WEAPONS VIOLATION DRUG SELLING DRUG USE PROPERTY PUBLIC ORDER SEX NON-
VIOLENT TRAFFIC VIOLENT VIOLENT SEX VOP/VOAC/VOAP WEAPONS VIOLATION DRUG USE STATUS VOP/VOAC/VOAP

Race
White White White White White White White White
White
White White White White
White
White White White White
White
White White White

Median Offense
Rank 29.5 35 28 41.5
8 10.5 30
32
54 59 61
59
63.5 53 51 70
55
71 71 71

Number of
Crimes 7 1 57 13
19 3 5
6
22 38 57
1
26 33 1 69
2
4 41 15

Race
Black Black Black Black Black Black Black Black
Black
Black Black Black Black
Black
Black Black Black Black
Black
Black Black Black

Median Offense
Rank 24 36 30.5 36.5 23.5 10 10.5 30
34.5
58 56.5 59 60
59
63.5 53 51 70
55.5
71 71

Number of
Crimes 16 33 405 113 4 213 11 19
36
1 34 151 350
46
19 175
5 403
20
63 251

Difference in Offense
Rank 5.5 -1 -2.5 5
-2 0 0
-2.5
-2.5 0 1
0
0 0 0 0
-0.5
71 0 0

RRI
2.113219 30.50961 6.569054 8.03633
10.36451 3.389956 3.513227 5.547201
1.428824 3.673804 5.67696 42.52854 0.675621 4.902829 4.622667 5.399812 9.245335
0 1.420625 15.47053

DMC Assessment Report April 2012

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Table 10. Reduced RRIs based on Offense Data, for Black youth

Chatham Clayton DeKalb Fulton

Total RRI
6.90 2.45 16.14 24.20

Mobility Effects RRI
5.21 1.78 10.56 17.08

Gwinnett

3.35

3.13

Newton

3.33

2.76

*These crimes are listed in the body.

Without these crimes* 4.37
8.21 9.49
2.6
2.12

Percentage Explanation in RRI
36.7%
49.2% 60.8%
22.5%
36.3%

DMC Assessment Report April 2012

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Table 11. Data Availability

Court Data from

DJJ

Juvenile arrested

0

Juveniles Referred

Juveniles Diverted

0

Juveniles in Secure Detention

Juveniles Petitioned

0

Juveniles result in Delinquent Findings

0

Juveniles Committed to DJJ

Juveniles in Confinement

Juveniles sentenced to Adult Court

*Data for Secure Detention and Confinement are incomplete

GOCF*

DJJ Clearinghouse 0

0

0

DMC Assessment Report April 2012

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Map 1. Black Referrals and Schools' Overall Percent with Free and Reduced Lunch and Black Enrollment