Assessing Racially Biased Policing: Benchmark Tool Delivers Improved Methods to Police Departments
Over the years, in response to allegations of racially biased police practices, many police departments began collecting information on officer traffic stops. Social scientists, in turn, have used these administrative data on stop activities to assess the existence or extent of racially biased policing; in the process, they have developed a number of benchmarks against which particular police stop data can be compared.
A chapter by RAND researchers in a new book on race, ethnicity, and policing describes and assesses an array of benchmarking methods--both internal and external--including the use of U.S. Census population estimates, non-at-fault driver crash data, crime and arrest data, drivers' license data, red-light cameras, observations, instrumental variables, assessments of post-stop outcomes, and officer-to-officer comparisons through internal benchmarks. The RAND researchers note that while all methods have weaknesses, substantial improvements have been made over time.
But departments and their analysts have been slow to adopt these improved methods. So, to facilitate their adoption, RAND has created the RAND Benchmarking Tool, available as a web service at benchmark.rand.org. The tool, originally adopted by the Cincinnati Police Department, customizes benchmarks for individual police officers based on the time, place, and context of their activities. Using stops conducted by other officers patrolling at the same times and in the same places and context, the tool can flag officers with atypical stop patterns. For access to the online benchmarking tool, contact Laura Selway at email@example.com or (703) 413-1100, ext. 5423.
READ THE CHAPTER REPRINT: Methods for Assessing Racially Biased Policing
VIEW THE RELATED VIDEO: Racial Profiling Analysis in a Post-Beer Summit World
READ THE RELATED TESTIMONY: Summary of the RAND Report on NYPD's Stop, Question, and Frisk
RAND RELATED REPORT: Cincinnati Police Department Traffic Stops: Applying RAND's Framework to Analyze Racial Disparities
READ THE RELATED RESEARCH BRIEFS: Do NYPD's Pedestrian Stop Data Indicate Racial Bias? | Efforts to Improve Polic-Community Relations in Cincinnati | Assessing Racial Profiling More Credibly: A Case Study of Oakland, California
RAND RELATED COMMENTARIES: The Decline of Racial Profiling | Police Need to Do a Better Job of Explaining Stop-and-Frisk | Racial Profiling Won't Stop Terror | Measuring Racial Profiling by Police | Police-Search Statistics Don't Lie, but Statisticians Can
Understanding the Public Health Implications of Prisoner Reentry in California
When former inmates return to their communities, what are the public health implications to those states and localities? This has become a key question for California, in particular, because the landscape for assessing the public health implications of prisoner reentry in in that state has changed dramatically over the past few years. First, California is in the midst of a deep and persistent recession, which has significantly weakened the health care safety net on which ex-prisoners rely. Second, California's 2011 Public Safety Realignment Plan--which shifts responsibility for low-level offenders away from the state and onto counties--will have a number of implications for meeting the health care and rehabilitation needs of the reentry population. Finally, the implementation of the Patient Protection and Affordable Care Act will expand Medicaid eligibility and thus help remove a key barrier to access to care for the reentry population.
A new RAND study helps inform planning for these policy changes by examining the specific health care needs of California's reentry population, the public health challenges of reentry in California, and the policy options for improving access to health care safety-net resources for this population in the context of significant policy changes. Key findings include the following:
- California inmates' health care needs are high; mental health and drug treatment needs are even higher.
- Certain California counties and communities are particularly affected by reentry, and access to safety-net care for health, mental health, and substance abuse problems varies across California counties, within counties, and by race/ethnicity.
- The ongoing financial crisis has further weakened the state's health care safety net, exacerbating existing issues for reentering prisoners and their families and for providers offering services to the reentry population.
- California's 2011 Public Safety Realignment Plan and the advent of health care reform present challenges and opportunities for addressing ex-prisoners' reentry and health care needs.
- States and counties must closely coordinate their efforts to leverage resources and put into place the necessary service delivery strategies to implement both the realignment and health care reform measures.
The study concludes with some recommendations at both the state and county levels.
READ THE REPORT: Understanding the Public Health Implications of Prisoner Reentry in California
READ THE RELATED RESEARCH BRIEF: Assessing Parolees' Health Care Needs and Potential Access to Health Care Services in California
READ THE COMMENTARIES: California's Prisoner Shuffle | Prison Health Care
Greg Ridgeway is director of the RAND Safety and Justice Program and of the RAND Center on Quality Policing, charged with managing RAND's portfolio on policing, crime prevention, courts, corrections, and public and occupational safety. He has worked with dozens of law enforcement agencies, local police, federal agencies, and non-U.S. police forces on predictive policing, recruiting, gun violence, community relations, use of force, racial profiling, and other key policing issues. He has also worked with the federal courts and other components of the justice system. His paper presenting a method for assessing racial profiling received the American Statistical Association Outstanding Statistical Application award in 2007. Prior to joining RAND in 2000, Ridgeway worked on data mining at Microsoft Research, receiving seven patents for developed methods. He received his Ph.D. in statistics from the University of Washington, Seattle.
Read more about Greg Ridgeway »
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