Presentation on theme: "REDUCING RACIAL AND ETHNIC DISPARITIES: USING DATA TO PROMOTE REFORM Dana Shoenberg, Deputy Director, CCLP Tiana Davis, DMC Policy Director, CCLP NJJ N."— Presentation transcript:
REDUCING RACIAL AND ETHNIC DISPARITIES: USING DATA TO PROMOTE REFORM Dana Shoenberg, Deputy Director, CCLP Tiana Davis, DMC Policy Director, CCLP NJJ N Webinar, February 12, 2014
Leads a national movement State-based juvenile justice coalitions and organizations (43 members in 33 states) Laws, policies and practices that are fair, equitable and developmentally appropriate for all children, youth and families Photo: MorizaMoriza Brought to You By …
Our Speakers Dana Shoenberg Deputy Director of the Center for Children’s Law and Policy Tiana Davis DMC Policy Director at the Center for Children's Law and Policy
Agenda Goals and strategies of RED reduction Importance of local, data-driven change The Relative Rate Index: Uses and Limitations Examples of decision point data and what they can be used for Opportunities for advocates
Goals in addressing racial and ethnic disparities 1. Reducing over-representation 2. Reducing disparate treatment 3. Reducing unnecessary entry and moving deeper into the juvenile justice system We want to address all three goals.
The Juvenile Justice Process: Key Decision Points and Pathways Out Arrest: Law enforcement Schools Probation Child welfare Referral: Intake staff Detention: Judge Transfer to adult court Petition: Prosecutor Adjudication: Judge Disposition : Judge Diversion Community service Youth court Diversion Informal process Consent decree Diversion Release home Alternative to detention Diversion Informal process Dismissal Diversion Post-adjud ATD Dismissal Probation Non-secure placement Non-residential treatment
Collaboration and Cross System Collaboration Improve collaboration and communication among agencies within the juvenile justice and with other child-serving systems Data Practices Establish a structure and process for regular use of data in system management Culture and Community Improve cultural competence and responsiveness of juvenile justice services and engaging community in those efforts Policy and Practice Structure policies, protocols and tools to facilitate objective and consistent decision-making Program Access Increase capacity and improve access to programs and services that prevent deeper involvement or enhance diversionary pathways out of the juvenile justice system Strategic Approaches for Reducing Racial and Ethnic Disparities 9
Local, Data-Driven Change
Effective RED change Like politics, effective RED change happens at the local level. Efforts should be led by county/parish-based collaboratives that include all stakeholders -- family members, child-serving agencies and community representatives as well as those who work inside the juvenile justice system. Diverse perspectives lead to healthy conversations and opportunities for change in more realms
Clergy Community Service Providers Community Activists Defense Attorneys Youth Judges Juvenile Probation Officers Parents Police Prosecutors School Systems Diverse Governing Body for RED Reduction
Data-driven Decision Making Activities chosen and informed by decision point data New policies and programs assessed for effectiveness Continuous use of data to inform court and probation operations
Why lead with data? Avoids getting lost in anecdote Supports honest conversations about real differences Provides structure for digging deeper and understanding the problem (peeling layers of the onion)
Key data: Decision Points Arrest Referral to Juvenile Court Diversion Secure Detention Petition Delinquent findings Probation, Probation Violations Out of Home Placement Secure Confinement Aftercare, Revocations Transfer
Key data for each decision point Race Ethnicity Gender Geography Offense For programs and placements: Length of stay Whether successful completion If unsuccessful, reasons why Demographics and CharacteristicsExperience of youth by group
Qualitative and Quantitative Data Sometimes the numbers (quantitative data) aren’t enough. To learn more, need to ask stakeholders about their experience (qualitative data) Formulate questions, conduct interviews
Use of Qualitative and Quantitative Data Ex: Youth of color are overrepresented among school referrals Examine quantitative data on types of offenses, ages, times of day, particular schools Interview SROs, youth, families, teachers, principals to understand how things work in practice When are SROs called What is their understanding about their role How much training do teachers have in classroom discipline What alternatives to arrest are available What message does the administration send about appropriate use of SROs Level of interest in new options
Race and Ethnicity Disaggregation Hispanic/Latino is an ethnicity U.S. Office of Management and Budget (OMB) recommends collecting information about race separate from ethnicity Two questions: Are you Hispanic/Latino or Non-Hispanic/Latino What race do you identify with?
Race and Ethnicity Reporting Two-question format allows for reporting both: White Non-Hispanic, White Hispanic, Black Non-Hispanic, Black Hispanic, Asian Non-Hispanic, Asian Hispanic, Native American Hispanic, Native American Non-Hispanic Be careful of data reports that separate the reporting, for example: Non-Hispanic/Latino 45%, Hispanic-Latino 55% White 50%, Black 30%, Asian 5%, Native American 15% Be careful of data reports that only capture race – erases the Latino population and creates a white overcount, masking disparities
Relative Rate Index (RRI) Rate = number of youth in that group at decision point number of youth in that group at prev. dec. pt. Relative rate = rate rate RRI compares rate of youth of color to rate of white youth at particular decision point Calculates the rate at specific decision point using information from the immediately previous decision point
Relative Rate Index -- Example Youth population:1,000 White population:800 Black population: 200 Total arrests:100 White arrests: 20 Black arrests:80
Relative Rate Index -- Example Relative Rate Index calculation: # of Black youth arrested 80 =.400 # of Black in population 200 ____________________________ (÷) # of White youth arrested 20 =.025 # of White youth in pop = 16 RRI.025
Uses and Limitations of RRI If the relative rate is significant, it shows an obvious point where you could focus attention Where most of the youth in the jurisdiction are youth of color, RRI won’t mean much Low RRI may mask potential opportunity to impact many youth Doesn’t explain reasons for disproportionality – still need to dig deeper Some RRI data resources don’t capture ethnicity UsesLimitations
RRI example Decision Point African American Hispanic/La tino Native American Asian/Pacifi c Islander All Youth of Color Arrests Referral Diversion Secure Det Petition Delinquent Findings Probation Placement Secure Conf * Transfer **1.03
A Case Study in Peeling the Onion at Arrest: Sedgwick County, Kansas
Top 3 Arrest Offenses in 2008 for African-American Youth
Comparison: 2007 – 2008 Arrests by Gender
. Arrests for Theft <$1,000 – Analysis by Geography Not surprisingly, a majority of Theft <$1,000 arrests occurred at the two large malls in Sedgwick County
The Response Collaborative and Data Driven The county’s stakeholder group developed a work plan and goals based on data collected Interventions An anti-Shoplifting Campaign emphasized theft deterrence and controlling peer influence using local girls as ambassadors Enhanced diversion policies targeted youth charged with theft <$1000 offenses Realigned and enhanced diversion programs (Girl Empowerment Program) incorporated research-supported shoplifting interventions
Sedgwick County Results: Arrests for Theft <$1,000 Data reflect a 31% drop in arrest for White youth, 26% drop for African American youth and an 18% drop for Hispanic youth.
Havenhurst Court Family Domestic Violence Referrals by Race and Offense BlackHispanicWhiteGrand Total ASSAULT 1ST DEG100 1 ASSAULT 2ND DEG010 1 ASSAULT 3RD DEG422 8 BREACH OF PEACE 2ND DEG303 6 CRIMINAL MISCHIEF 2ND DEG010 1 CRIMINAL MISCHIEF 3RD DEG300 3 DISORDERLY CONDUCT INTERFERE WITH OFFCR/RESISTING100 1 RECKLESS BURNING001 1 STRANGULATION SECOND DEGREE200 2 THREATENING 2ND DEG220 4 Grand Total
Family Domestic Violence Referrals to Havenhurst Court by Resident City and Race* *Total number of Havenhurst referrals =41. Domestic Violence Referrals to Juvenile Court
Rate of Judicial Handling for Top 3 DV Offenses* by Race Rate per 10 ReferralsRelative Rate Index White4.31 Black Hispanic *Top 3 DV Offenses include Disorderly Conduct, Assault 3 rd and Breach of Peace 2 nd. Black youth are almost twice as likely to receive Judicial Handling.
Possible Next Steps: Havenhurst Domestic Violence Referrals Learn about intake practices How are handling decisions made? Judicial vs. Non-Judicial What diversion opportunities are available for youth referred to court for domestic violence offenses? Collect additional data to inform understanding of the domestic violence referral population What are the characteristics of cases excluded from non- judicial handling eligibility? Are there differences by race, ethnicity, gender, geography, or offense?
Possible Next Steps: Havenhurst Domestic Violence Referrals Learn about experiences of youth and families referred to court for domestic violence offenses. What led to the referral? What could have helped to avoid the referral Interventions could include: An objective tool to assess risk of re-offense and identify service needs. A clear and concise diversion policy for domestic violence related offenses. Domestic violence diversion programming that is culturally appropriate and responsive to the needs of key populations.
Buttercup County Detention Data
Observations for Buttercup County 35% of detentions are probation violations, mostly youth of color Compared with new arrests, Hispanic youth are overrepresented among warrants
Possible Next Steps: Buttercup VOP Learn about probation practice – graduated responses? Alternatives to detention? Learn about youth and family experiences on probation – cultural and linguistic competence? Adequate programming and attention? Collect data on kinds of probation violations Interventions could include: institution of graduated responses, increase skills of probation staff, increase staffing levels, reform case planning, establish new ATDs, find new linguistically competent partners
Possible Next Steps: Warrants Collect data on reasons for warrants and offenses of youth who have warrants If warrants for Failure to Appear, interview families, judges, probation about reasons for Failures to Appear Interventions could include tiered warrants, call reminder/notification, rapid processing of warrants
Osage County Placements Race/ethnicityLength of Stay Caucasian85 Hispanic/Latino98 Native American125 African-American90 Asian102
Osage County – Learning More Second level data analysis: Individual programs’ length of stay Numbers of youth represented in length of stay data – are these anomalies or significant numbers? Qualitative data: Discipline structure in programs – does it affect length of stay? What input do courts have into length of stay and how frequently do they review cases Determinate sentences or “when she completes her program?”
How to Connect with Existing RED/DMC Reduction Efforts OJJDP State Contacts State and Local DMC Coordinators and DMC Subcommittee Chairs 3-Year Juvenile Juvenile Justice Plans State Advisory Groups (SAGs) Many available online Outline the key activities to address DMC/RED in your state.
How to Connect with Existing RED/DMC Efforts Juvenile Detention Alternatives Initiative (JDAI) More than 200 jurisdictions in 39 states nationwide JDAI sites focus on RED as Core Strategy for Detention Reform Models for Change Initiative Center for Children’s Law and Policy change.html change.html
What if there isn’t an RED reduction effort yet in your area? Start a collaborative – to engage stakeholders, think about what their interests and points of view might be Access to data can be hard – both because it isn’t available and because of lack of trust. Consider: Information-sharing agreements and protocols Engaging a university that can help develop and analyze the data if the court doesn’t have expertise or time in-house Offering to do the analysis if they’ll just provide the numbers