This second edition of The Enhancing Law Enforcement Response to Victims (ELERV) Strategy, which was released in 2020, includes comprehensive updates to the original ELERV Strategy package, highlighting information gained and lessons learned from the three agencies that implemented the ELERV Strategy between 2014 and 2019.
The ELERV Strategy introduces federal, state, local, campus, and tribal law enforcement leaders to the benefits, challenges, and methods for adopting victim-centered, trauma-informed philosophies intended to improve their response to crime victims. The focus is on understanding and addressing the following critical crime victim needs: safety, support, information, access, continuity, voice, and justice. Law enforcement agencies can address these needs by understanding and implementing the four core principles of the ELERV Strategy: leadership, partnering, training, and performance monitoring. Leadership involves developing and sustaining an agency infrastructure that prioritizes effective response to victims. Partnering facilitates understanding and facilitating victim services through agencies that specialize in various victim services. Training is required for all ranks, disciplines, and career stages to ensure that victim services are sustained, timely, and effective. Performance monitoring involves structuring data collection and analysis that assists in determining that victim services are consistently provided and are effective. This second edition draws on the beneficial experiences, lessons learned, and challenges experienced by ELERV pilot sites, validation sites, and demonstration sites. Online access is provided to various resources related to the features and implementation of ELERV.
- Exploring the Neighborhood-Level Impact of Retail Marijuana Outlets on Crime in Washington State
- Assessing Risk of Terrorist Acts by Looking at Location Data and Demographic and Social Characteristics
- Identification of Minor Dye Components of Fibers via Integrating-Cavity-Enhanced Raman Spectroscopy