This is one in a series of blogs focused on Gun Violence Awareness in June. To connect with NLC’s Justice Initiatives Team and other cities working to address violence in their communities, email us at justiceinitiatives@nlc.org.
Data-Informed Community Engagement (DICE) pairs crime data and analytics with community-driven risk narratives, empowering cities to coordinate public safety strategies and initiatives. The first step of DICE is to analyze crime patterns using Risk Terrain Modeling (RTM). RTM uses geospatial data and analytics to diagnose environmental conditions that lead to crime, identifying key neighborhood places with a high risk of violence. Then, DICE coordinators conduct deep listening and outreach to residents and members of the community to construct risk narratives or stories about the context of violence in these places.
Pairing crime data with community-driven risk narratives then paves the way for stakeholder coordination, empowering local agencies and support organizations to address crime through targeted, place-based interventions. In this way, community organizations become “co-producers of public safety,” encouraging a comprehensive and community-centric approach to crime interventions.
DICE, first developed by Joel Caplan, Dr. Alejandro Gimenez-Santana and Dr. Leslie Kennedy at Rutgers University, was tested through the Newark Public Safety Collaborative (NPSC) and replicated in Dallas through the Child Poverty Action Lab (CPAL).
Caplan and Kennedy also published a study evaluating five cities employing RTM and the DICE approach to place-based crime prevention: the researchers found that neighborhoods implementing DICE identified a 35 percent reduction in gun violence, 42 percent reduction in robbery, and 33 percent reduction in motor vehicle theft in the target areas compared to the control areas.
Source: PolicingEquity.org (PDF)
Municipality Highlights: DICE In Action
Newark, NJ: Newark Public Safety Collaborative
The Newark Public Safety Collaborative (NPSC), formed in 2018, uses geospatial analysis techniques to help empower community organizations and other local stakeholders to develop and implement crime prevention strategies.
Receiving raw crime data from the Police Department, NPSC analyzes the data to “ensure that the data can be used by partners to implement strategies and make resource allocation decisions.” In an NLC Webinar held on May 23, 2024, ‘Using Data-Informed Community Engagement for Safer Cities,’ Adriana Santos, Manager of NPSC, stated, “Data is only useful if the community understands it and can use it.”
Nearly Half of NPSC Partners are Community-Based Organizations
NEWARK PUBLIC SAFETY COLLABORATIVE PARTNERS AS OF MAY 2024
For over five years, NPSC has convened partners on a bimonthly basis to turn data and analysis into mobilized community resource responses. NPSC leaders stress that data is only a first step in problem-solving and that the purpose of the broader meetings is to unveil narratives around why crime is concentrated in certain places. With all community partners having a seat at the table, stakeholders can coordinate community-led, data-informed strategies and co-produce community responses to promote public safety in specific areas of the city.
NPSC Analytics in Action
NPSC partnered with local utility company PSE&G to replace outdated halogen streetlights with newer, brighter LED lights in order to reduce nighttime crime.
Source: NPSC (PDF)
NPSC, using data and analytics, identified specific areas of Newark with the highest risk of criminal behavior during the night. NPSC then prioritized these street light areas for PSE&G utility upgrades. Post-upgrade, areas with replaced street lighting observed a 35 percent decrease in violent crime incidents compared to the control group, and no homicides were observed within 200 feet of enhanced streetlight poles. By pairing data with the expertise and resources of local partners, NPSC’s place-based DICE approach contributed to a safer city.
Dallas, TX: Child Poverty Action Lab
Dallas’ Child Poverty Action Lab (CPAL) works across various policy areas to center data and lived experiences with the goal of reducing childhood poverty in the city. To address poverty at the neighborhood safety level, CPAL uses violent crime data and RTM that analyze environmental features that may contribute to poverty, violence, and/or a lack of structural investment. The CEO of CPAL, Alan Cohen, was one of the co-chairs of Dallas’ Mayor’s Task Force on Safe Communities Report. CPAL conducted the analysis for the report, which became the impetus for the community investment and violence reduction efforts happening in the Dallas Office of Integrated Public Safety Solutions.
CPAL Analytics in Action
In 2019, CPAL identified a vacant parking lot at the intersection of Malcolm X Boulevard and Marburg Street as the epicenter of violent crime in Southeast Dallas using RTM.
Source: DMagazine.com
Partnering with local community organizations, like the United Peoples Coalition and Better Block, CPAL led efforts to revitalize the vacant lot with mutual aid campaigns, family-friendly programming, summer camps, and community events.
Transforming the parking lot into a community plaza not only demonstrated the DICE approach in action but was also associated with safer outcomes for the neighborhood.
The Malcolm X and Marburg area reported a 23 percent reduction in crime in 2021 relative to 2019, which greatly outpaced the city-wide decrease of 5 percent. Moreover, arrests decreased in the area by 59 percent.
Source: NBCDFW.com
Since the initial community-led success, CPAL has replicated this approach in other neighborhoods.
The Role of Local Leaders: Turning Data into Action
DICE is a hyper-local, community-driven approach tailored to specific places, but the DICE and RTM models have been prioritized at the federal level. In 2022 remarks, Associate Attorney General Gupta announced DOJ funding for the NPSC DICE model, stating, “To evaluate problems, inform solutions, and measure success, we must collect accurate and comprehensive data and make that data usable and widely accessible.” In the NLC webinar, ‘Using Data-Informed Community Engagement for Safer Cities,’ Rachel Tache, Chief of Neighborhood Insights, CPAL, and other Local DICE leaders explained that data is a centering tool for city partners; by level-setting and leading with data, it can act as a shared language for many groups pursuing measurable goals.
It is the role of local leaders to promote a data-informed, community-led approach to public safety by fostering this kind of ecosystem. Municipal leaders can promote data sharing between agencies, pave the way for collaborative partnerships, and ensure public safety data is used responsibly and complemented by community narratives.
Community-led Approaches to Public Safety
NLC’s Municipalities Reimagining Community Safety (MRCS) Initiative, launched in 2022, advances the work in cities to expand the use of civilian-led and community-based public safety initiatives, promoting data-driven solutions through peer learning. Bringing together local officials, city leaders across public health and safety departments, community organizations and residents themselves, MRCS champions collaborative city safety efforts that prioritize local needs – with a specific focus on data (collection, transparency and management systems).
The City of St. Louis created the Office of Violence Prevention and has convened community organizations to discuss the city’s challenges and strategize partnerships for violence prevention; the City is also working to build capacity within the OVP and in community partners for a collaborative data management system.
Source: StLouis-MO.gov
Moreover, the Baltimore Mayor’s Office of Neighborhood Safety and Engagement (MONSE) has expanded its community violence intervention ecosystem (PDF) while bolstering a strong data management system that increased the efficacy of violence prevention programming. Much like the DICE approach, MRCS works with cities to promote collaboration, data storytelling and community engagement for public safety.
DICE uses RTM to diagnose crime patterns in hyper-specific locations. Data and analytics, however, are only one part of the DICE model; the human element of residents, community-based organizations, and deep listening to build risk narratives ensures that DICE is tailored to local problems and lived experiences. This makes DICE a holistic approach to public safety and ensures that DICE turns analytics into action for safer cities overall.
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