Crime Prevention with Data-Informed Community Engagement

Crime Prevention with Data-Informed Community Engagement
Duration: 60 Minutes
Module 1Module 1
Recorded on: 2021-04-20
Unit 1Slide Deck: Crime Prevention with Data-Informed Community Engagement
Unit 2Transcript: Crime Prevention with Data-Informed Community Engagement
Unit 3Workbook: Crime Prevention with Data-Informed Community Engagement
Unit 4Recording: Crime Prevention with Data-Informed Community Engagement

What happens when you merge factors of evidence-based and community policing together? Well, you get a super-informed strategy to mitigating and managing crime and other issues that a community might face. This webinar will expound on the how of this topic by introducing Data Informed Community Engagement (DICE), Risk Terrain Modeling (RTM), and Risk-Based Policing (RBP).

This session’s instructor is Joel M. Caplan, a professor at Rutgers University School of Criminal Justice (SCJ), Director of the SCJ Master’s Program, and Director of the Rutgers Center on Public Security (RCPS). He co-developed RTM to help agencies prevent crime, improve community policing, and develop policies and programs to enhance public safety.

Topics of discussion include:

  • Data Informed Community Engagement as the instrument that allows the delineation of the different components required to create an effective and holistic community strategy against its issues.
  • The concept of connecting geographic features with crime locations to help enforce the best strategies for mitigation and prevention, also known as Risk Terrain Modeling.
  • An example of an RTM map that displays where crimes are happening, how these are clustered geographically, and its proximity to specific key environmental features and infrastructures.
  • Recognizing Risk-Based Policing as the application of DICE and RTM led by law enforcement.
  • The three primary data needs to conduct an RTM analysis and where to obtain these.
  • Different ways the data can be customized into reports and can be turned into recommendations and action plans towards an identified goal.
  • Leveraging the results of RTM in report-taking and problem-solving.
  • Understanding risk narratives that result from RTM analysis and the identified risk factors.
  • Case examples and demonstrations were provided showing:
    • How Newark, New Jersey’s Public Safety Collaborative utilized RTM to identify the risk places for aggravated assaults and by doing so, allowed community partners to flip abandoned buildings into affordable housing and other usable spaces.
    • How Kansas implemented RBP and reduced violent crime significantly with the help of the fire marshal, code enforcement, and transit authority.
    • Philadelphia’s data when it comes to shooting incidents and the environmental features that intersect with these incidents to identify risk factors.
    • Atlantic City PD’s RTM that generated priority areas for each division allowing its officers to focus on specific assignments when deployed and decreased robberies remarkably.
    • How convenience stores, vacant buildings, and laundromats create a risk narrative that links shootings to drug trade.
    • How the Newark police employed the help of businesses to minimize risks at and around ATMs.
  • How DICE, RTM, and RBP helped unburden law enforcement and create a more effective strategy by mobilizing more community stakeholders in addressing common community crime issues.
  • How to replicate the DICE for your jurisdiction by following a straightforward process.

Questions from the audience are about:

  • Typical agency partners that law enforcement works with.
  • Risk factors identified when using RTM on overdose analysis.
  • Jurisdictions that have used RTM.
  • RTM’s difference to predictive policing.
  • Best practices when trying to access data for RTM purposes.
  • Accessing the RTM software.
  • Newark’s choice to utilize abandoned properties for low-income housing.
  • Integrating RTM with an existing database, software, or systems.
  • Implementing RTM when some of the needed data aren’t available.

 

 

 

Click here to view and register for other upcoming ASEBP webinars on the JCH Platform.

 

Resources and Handouts

 

Audience Comments

  • “Great information provided. Would like to of had more information in other programs the RTM model has helped agencies.” — Billy
  • “The material was very informative.” — Anthony
  • “I have used Google Earth for many applications and usually draw or drop information on the geographical image. I like the idea of really layering multiple informative notes and images to show problem areas or needs.” — Carl
  • “Very knowledgeable speaker and well ordered, understandable presentation even for an older ‘non-tech’ person. Thank you!” — Bob
  • “We don’t used DICE, but we have similar procedures in place and find them very beneficial in preventing crime.” — Ken
  • “Putting a new perspective on the use of social factors in addition to stats data.” — Brian
  • “Using RTM to diagnose the “risk narrative” and use creative thinking to involve other groups/stakeholders to contribute to disrupting that narrative and ultimately reducing crime. Also, this is not just a Law Enforcement issue, other city services and local organizations are stakeholders and using RTM is helpful in getting them to understand their “part of the narrative” and hopefully to take action towards the common goal of crime reduction.” — Nina

 

Additional Resources
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After the Webinar: Crime Prevention with Data Informed Community Engagement. Q&A with Dr. Joel Caplan
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