By The Organization for Security and Co-operation in Europe

This paper is a summary of the first of a series of roundtable discussions that aim to identify opportunities for law enforcement to harness new technologies to support its work, help formulate policy recommendations and explore potential OSCE capacity-building support in this area. The first event of this series was dedicated to the topic of harnessing new technologies to enhance crime analysis, and focused on opportunities and challenges in deploying artificial intelligence (AI) for analysis and the potential impact of these technologies on human rights.

\

Prague: OSCE 2025. 12p.

By Brian A. Jackson, Pauline Moore, Jennifer T. Leschitz, Benjamin Boudreaux, Jo Caulkins, Shoshana R. Shelton

Violence by K–12 students is disturbingly common. Ensuring that schools have effective ways to identify and prevent such incidents is becoming increasingly important. Various concerning behaviors or disturbing communications, including direct threats, can precede acts of violence. Although removing every student exhibiting such behaviors might seem prudent, doing so can be counterproductive, limiting the effectiveness of safety efforts. With effective systems for behavioral threat assessment and management (BTAM), schools can assess and respond to concerning behavior to protect the community and respond to the student whose behavior caused concern.

To do so, schools need the tools to respond. Tools may include restrictive measures or law enforcement involvement in the most serious cases, but other options can be more effective. Those additional options include different types of mental health intervention, counseling, and other supports. Teams with extensive tools available to them can better customize interventions, increasing the chance of positive outcomes for all involved.

In this report, the authors draw on published literature and extensive interviews with education and public safety practitioners to build an inventory of the many intervention options that are valuable for schools in the management phase of BTAM. In addition, drawing on varied approaches from the fields of counseling, school discipline and behavioral management, and other professions that must match appropriate services to the needs of youth in their care, the report discusses decision support tools to help management teams implement this critical part of efforts in preventing targeted violence and keeping school communities safe.

Key Findings

Various Intervention Options Are Available for K–12 BTAM Efforts

Support-focused interventions can address the underlying causes of problematic student behavior and also lead a student toward a more favorable, positive path into the future.

By using supportive counseling and other interventions, BTAM is widening the options available for school leaders and staff to address problematic behavior that has the potential to develop into violence.

To be effective, school BTAM teams need a broad set of tools, including options appropriately matched (1) to the specifics of a student's problematic behaviors, (2) to the unique school community and environment, and (3) to the needs and circumstances of the student or students involved.

Insights from Education, Public Safety, and Other Fields Can Be Combined to Support Matching Effective Interventions to Student Needs

Decision support tools and resource-matching guidance can help ensure that school-based teams are collecting the information required to taking a holistic approach to address a student's varied needs and help promote appropriate consistency to ensure that disparities in how BTAM teams respond do not substantiate concerns that BTAM processes are unfair or inequitable.

Using structured systems to capture data when a BTAM team (1) interviews students involved in an incident, (2) collects school or law enforcement data, or (3) contacts others for information about a student of concern provides a more straightforward starting point for selecting among multiple intervention options.

Recommendations

To better inform intervention planning, intervention tools should be designed so that they prioritize collecting data on factors that can be changed because pieces of information in BTAM that may be a useful part of assessing the danger posed by an individual may be useless for intervention planning.

The inventory of intervention options developed in this study could provide a starting point for schools to make conscious decisions as they (1) review the options available to their teams and (2) identify any options they do not have access to but that could become valuable near-term priorities to strengthen their school safety efforts.

Progress monitoring data of BTAM efforts can help better support students while also helping schools become more responsive to external oversight of their BTAM programs and allay concerns about the fairness and equity of outcomes across different student populations.

Including positive mileposts into threat management planning not only could help lay out a path to full completion of all intervention activities but could also help define goals more specifically for an at-risk student, motivating even more beneficial outcomes.

Santa Monica, CA: RAND, 2025.

By National Academies of Sciences, Engineering, and Medicine

Mental, emotional, and behavioral (MEB) disorders—including mental illness and substance use disorders—are at the heart of several ongoing national crises and affect every U.S. population group, community, and neighborhood. Existing infrastructure responds to these crises predominantly with treatment and recovery, or addressing MEB disorders once they already exist, rather than working to prevent them. Available prevention services are insufficiently funded, fragmented, and better developed for substance use prevention than mental health promotion and for children and youth than for other age groups. Improved prevention services could help people thrive, avert the harms that accompany MEB disorders, and reduce the burden on an already overtaxed system. In response to a request from the Centers for Disease Control and Prevention (CDC), the National Institutes of Health (NIH), and the Substance Abuse and Mental Health Services Administration (SAMHSA), the National Academies of Sciences, Engineering, and Medicine (the National Academies) convened a committee of experts to develop a blueprint, including actionable steps for building and sustaining an infrastructure, for delivering prevention interventions for behavioral health disorders. The committee’s report, Blueprint for a National Prevention Infrastructure for Mental, Emotional, and Behavioral Disorders, presents its conclusions and recommendations. The committee asserts that the existing MEB disorder prevention infrastructure—partially present in other systems like education, health care, and human services—provides a foundation to build on and that creating another system would be inefficient. Instead, the report’s conclusions and recommendations focus on strengthening, coordinating, and funding existing structures to close gaps, prepare workers, and maximize available data to deliver needed interventions .

Washington, DC: The National Academies Press. 2025. 384p

By Emma,Sutherland Disley, Alex,Sussex, Jon,Pollard, Jack,Saunders, Catherine L.,Morley, Katherine I.,Gkousis, Evangelos,Hulme, Shann

This report presents an outcome evaluation of the National Model for Liaison and Diversion (L&D) in England, which aims to identify and support vulnerable individuals within the criminal justice system (CJS) by linking them with appropriate health and social care services. The evaluation utilizes a novel, large-scale linked dataset, combining healthcare and criminal justice records, to assess the impact of the National Model on health service utilization, re-offending rates, diversion from the CJS, and the timeliness of court processes. Findings suggest L&D services engage individuals with multiple vulnerabilities, intervene at crisis points, and may increase diversion from custodial sentences. However, the evaluation found no overall reduction in re-offending following L&D referral.

Santa Monica, CA: Cambridge, UK: RAND, 2021. 232p.

By Daniel S. Lawrence, Will Engelhardt, Storm Ervin, Rudy Perez

Before the implementation of the Juvenile Justice Reinvestment Act in December 2019, North Carolina was the last state that still automatically charged 16-to-17-year-olds as adults in its justice system. In March 2014, a group of stakeholders from Durham County—led by then–chief district court judge Marcia Morey—started the Misdemeanor Diversion Program (MDP) to prevent 16-to-17-year-olds from entering the justice system. The program has since expanded to include adults up to 26 years old. The first program of its kind in North Carolina, the MDP gives law enforcement officers in Durham County the discretion to redirect people accused of committing their first misdemeanor offense(s) to community-based services (such as life skills courses, restorative justice efforts, and behavioral health treatment) in lieu of citation or arrest. The purpose was to diminish unnecessary arrests and time in jail and the collateral consequences of being charged with and potentially convicted of a crime. What is particularly unique about this program is that it occurs prearrest and precharge, meaning someone law enforcement officers believe may have committed a crime will not be arrested or charged and will not formally enter the justice system in any way. This impact evaluation, the first conducted for the MDP, found that from March 2014 to February 2020, law enforcement officers in Durham County referred fewer than one-quarter of all people eligible for diversion to the MDP, though when they did, the program had positive impacts. In 2020 and 2021, with support from the John D. and Catherine T. MacArthur Foundation’s Safety and Justice Challenge Research Consortium, the Urban Institute conducted an in-depth impact evaluation of the MDP, the findings of which are detailed in this report. This impact evaluation was one component of Urban’s research on the MDP; Urban also conducted a detailed process evaluation that was described in a July 2021 report, A Process Evaluation of the Misdemeanor Diversion Program in Durham County, North Carolina (Engelhardt et al. 2021). Key Takeaways The data examined in this report cover January 2012 to February 2020 and were collected from North Carolina’s Administrative Office of the Courts, the MDP, the Durham Police Department (DPD), and the Durham County Sheriff’s Office. Box 1 provides five key findings the research team derived from these data. In this report, we assess the following: ◼ MDP enrollment ◼ MDP completion rates ◼ the MDP’s impact on new arrests, convictions, and jail admissions for program participants ◼ the MDP’s impact on disparities by race and ethnicity, sex, and age ◼ the MDP’s impact on system-level arrests, convictions, and jail admissions Analyses were separated into two population groups—people ages 16 to 17 and people ages 18 to 21—because each group was eligible for the MDP during different periods. These groups were statistically matched to comparison groups through propensity score matching for the analyses that examined new arrests, convictions, and jail admissions. The comparison groups were well balanced with the MDP participant groups (see appendix D) and were pulled from pools of people who were concurrently eligible for the program but did not participate. Five Key Findings ◼ Approximately 77 percent of people eligible for the MDP were not referred to the program while it was operational from March 2014 to February 2020. ◼ Of those who did participate in the program, there was a very high completion rate of 95 percent. ◼ MDP participants had significantly lower rates of rearrests, convictions, or jail admissions than comparison groups within six months, one year, and two years. ◼ Participation in the MDP significantly reduced disparities in new arrests within two years and in new convictions and jail admissions within six months between 16-to-17-year-old Black people and non-Black people, making the differences in the levels of new arrests between these groups much more equivalent than between Black and non-Black people who did not participate in the MDP. ◼ The MDP did not have a larger impact on countywide rates of arrests, convictions, or jail admissions for either of the two age groups we analyzed

Washington, DC: Urban Institute, 2021. 83p.

By Brittany C. Cunningham, Vincent Bauer, Kira Cincotta, Jessica Dockstader, Benjamin Carleton, Bridgette Bryson, Daniel S. Lawrence

Officer safety is of critical importance in an era of increased risk for law enforcement officers (hereinafter “officers”). Officers respond to some of the most unpredictable, traumatic, and violent encounters of any profession. Although much of an officer’s workday entails repetitive interactions, some calls for service or self-initiated contacts by officers may escalate into dangerous encounters. For officers to adequately mitigate the risks they may encounter while responding to calls for service, they must be well informed regarding the types of risks they face, the situations that may pose greater risk, and the strategies that will mitigate these risks.

Although previous empirical work on officer safety has yielded many important insights, to our knowledge, no prior work has applied machine learning models to produce risk assessments to promote officer safety. This project explored the potential for machine learning to identify high-risk incidents to officers using only the information available to dispatchers. A risk assessment model that could successfully flag high-risk incidents at dispatch would be immensely useful to law enforcement agencies, making it possible for officers to be better informed about potential risk factors before arriving on scene. Such a model would also be useful to agencies as they decide how to allocate scarce resources, such as deciding which calls should receive single- or dual-officer vehicles, where to send alternative response teams, and whether to deploy specialized units.

Readers should be aware that the model reflects the data upon which it is built. Biases in reporting and collecting officer injuries, as well as in how officers respond to calls for service, will be mirrored in the model’s risk assessments. While we have gone to great lengths to build the model using objective factors, these biases could sometimes lead the model to identify a situation as high risk when in fact that situation reflects low risk to officers. Concerns about the potential for bias in machine learning are important to evaluate, and these techniques offer opportunities for objective empirical examination of divisive topics to minimize the bias that is already present in the real world.

Calls for service and Law Enforcement Officers Killed and Assaulted (LEOKA) data were merged from each of the four agencies, revealing the following findings:

Overall, the machine learning model performed well, correctly identifying officer injuries about half of the time. Given the rarity of officer injuries within the four agencies, being able to identify half of such rare situations is notable.

The model was also able to identify the factors that were the most important in predicting risk to officer safety and the types of incidents that posed the highest risk to officer safety. The results demonstrate that such a model can identify officer injuries from data on call characteristics; thus, whether such a model could be built into the dispatch process should be explored so that officers would be informed about potential risk factors before arriving at the location of a call.

The model highlighted factors and calls for service types that posed greater risks to officer safety.

The results of the machine learning model, along with the results from the officer interviews and surveys, also highlighted an often-overlooked aspect of police operations that is critically important to officer safety: dispatch.

Beyond producing statistical models, this project also collaborated with participating agencies to explore officer perspectives on safety and identify promising practices and recommendations to reduce risks to officers.

This project provides several practical benefits for improving officer safety. These benefits include the following:

Quantifying concepts that until now have been only informally or qualitatively understood (e.g., the relative risks of different calls for service types).

Comparing officer perceptions about injury risk to the quantitative data and identifying where gaps in understanding exist.

Highlighting the important relationship between dispatch and patrol, as well as the implications that this relationship has for officer safety.

Helping agencies assess the efficacy of their trainings and policies that directly affect officer safety.

Providing guidance on the information agencies collect and make available to dispatchers.

Supporting agencies to improve the amount and quality of risk and injury data agencies collect and use.

We hope that by providing agencies with a foundational knowledge of risks to officer safety, agencies will have a basis for modifying policy, training, and operations, leading to the implementation of strategies, processes, and procedures to keep officers and the communities they serve safe.

Arlington, VA: CNA Corporation, 2024. 52p.

By Will Engelhardt. Storm Ervin, Daniel S. Lawrence, and Rudy Perez

Before its Raise the Age legislation in December 2019, North Carolina was one of the few states that still automatically charged 16- and 17-year-olds as adults in its justice system. In 2013, led by then–chief district court judge Marcia Morey, a group of stakeholders from Durham County, North Carolina, started the Misdemeanor Diversion Program (MDP) to prevent 16- and 17-year-olds from entering the justice system. The first of its kind in North Carolina, the program began in March 2014 and expanded over time to include people of all ages. It has also been replicated in certain counties throughout the state. The MDP allows law enforcement officers in Durham County to redirect people accused of committing their first misdemeanor crime(s) to community-based services in lieu of citation or arrest. The purpose is to diminish unnecessary arrests and time in jail, and the collateral consequences associated with being charged with and potentially convicted of a crime. What is particularly unique about this program is that it occurs prearrest and precharge, meaning someone law enforcement officers may believe has committed a crime is not arrested or charged and does not formally enter the justice system in any way. In 2020 and 2021, with support from the John D. and Catherine T. MacArthur Foundation’s Safety and Justice Challenge Research Consortium, the Urban Institute conducted an in-depth process evaluation of the MDP, the findings of which are detailed in this report. This process evaluation was one component of Urban’s research on the MDP; the research team is also conducting an outcome evaluation that will be described in a fall 2021 report.

Safely and Justice Challenge, 2021. 44p.

By: Michelle Kirby

A 2010 law established a pilot program to allow Connecticut courts to order GPS devices (ankle bracelets) to be used to track family violence offenders. Under this law, the Judicial Branch’s Court Support Services Division (CSSD) implemented the Alert Notification/GPS program in the Bridgeport, Danielson, and Hartford judicial districts. CSSD’s preliminary report on the program indicated that it met its objective to (1) enhance monitoring of high-risk family violence offenders and (2) increase victim safety. The December 2011 final summary report concluded that the program was successfully implemented in all three court locations with a high degree of collaboration systemwide.

Hartford: Connecticut General Assembly Office of Legislative Research, 2023. 4p.

By Eirik Jerven Berger 

Recent research on privileged drug offenders argues that they are at an advantage compared to marginalized people dealing drugs. The main question asked in this article is whether this is also the case in a more egalitarian country like Norway, and if it influences dealers’ decision-making. Findings reveal that privileged drug dealers believed they were at an advantage when it came to police and customers compared to people with an ethnic minority background or people dealing in open drug markets, but at a disadvantage in relation to violence and robberies. With regards to decision-making, believing they had advantages in encounters with the police informed their decision to be cooperative expecting fair treatment. Believing they were at an advantage with affluent customers in wealthy communities, and at a disadvantage with more street-oriented drug dealers, restricted privileged drug dealers' dealing to affluent low-risk contexts. The advantages and disadvantages privileged drug dealers talk about in interviews arguably reflect real-life drug market inequalities but are also a mechanism shaping decision-making that may reproduce drug market inequality. The study adds knowledge to the nascent literature on affluent drug dealers by introducing a novel case.

 European Journal of Criminology 2025, Vol. 22(1) 127–146

By Zoë Robinson and Stephen Rushin

The law enforcement lobby represents one of the most important and undertheorized barriers to criminal justice reform. We define the law enforcement lobby as the constellation of entrenched actors within the justice system—particularly police unions, correctional officer unions, and prosecutor associations—that exert an outsized role in policy development. The law enforcement lobby operates largely without coordinated opposition, resulting in capture of criminal justice policymaking and skewed policy outcomes that often institutionalize injustice and subordination. The strength of the law enforcement lobby also presents a challenge to the growing defunding and abolition movements. Nevertheless, the law enforcement lobby remains at the periphery of contemporary scholarly conversations about the democratization and design of criminal justice institutions.

This Article describes and evaluates the influence of the law enforcement lobby on criminal justice policy. It argues that the law enforcement lobby raises unique problems that extend beyond traditional lobbying concerns, including the ability to influence life and liberty, the power to perpetuate racial subordination, and a pervasive power over the operation of democratic institutions.

Drawing on the growing calls for democratization and power-shifting in the criminal justice system, this Article offers a range of recommendations to curtail the strength of the law enforcement lobby. First, the Article argues for reforms that “level up” of the power of competing interests that can counter the power of the law enforcement lobby in criminal justice policymaking. In doing so, the Article focuses specifically on reforms that imbed contestation in policymaking by communities most impacted by the criminal justice system. Second, the Article concurrently proposes mechanisms to “level down” the power of the law enforcement lobby, including realistic restrictions on the lobbying capacity of law enforcement interest groups that draws on First Amendment Speech Clause doctrine that permits restriction of public employee speech. Taken together, these reforms could facilitate broader transformation of the American criminal justice system.

107 Minnesota Law Review 1965 (2023), 73p.

B/y Griffin Edwards and

Stephen Rushin

In 1981, the U.S. Supreme Court held in New York v. Belton that police officers could lawfully search virtually anywhere in a vehicle without a warrant after the arrest of any occupant in the vehicle. Then, in 2009, the Court reversed course in Arizona v. Gant, holding that police could only engage in vehicle searches after such arrests in a smaller number of extenuating circumstances. This series of cases became a flash point for the broader debate about the regulation of policing. Law enforcement groups argued that administratively complex rules, like those established in Gant, risk officer safety. But some scholars and civil rights activists worried that by giving police officers wider discretion to search vehicles incident to arrest, the Belton rule may have led to unjustified civil rights violations and racial profiling.

This Article argues that, by limiting vehicle searches incident to arrest, Gant may have disincentivized policing tactics that disproportionately target individuals of color without jeopardizing officer safety.

By utilizing a data set of traffic stops from thirteen law enforcement agencies in seven states, this Article presents an empirical study of the effects of shifting doctrines related to vehicle searches incident to arrest. This Article makes two findings. First, it finds no evidence that Gant endangered officer safety. Changes in state doctrines related to vehicle searches incident to arrest are not associated with increases in assaults of officers during traffic stops. Second, it hypothesizes that Gant may have reduced racial profiling. Gant may be linked to a somewhat larger decline in vehicle searches incident to arrest for nonwhite individuals relative to white individuals.

These findings are a reminder that seemingly neutral procedural choices by courts in regulating police behavior may have racially disparate effects. We conclude by arguing for the narrowing of the discretionary authority of police officers as a mechanism for reducing disparities in the criminal justice system.

91 Fordham L. Rev. 1 (2022).

By Pradhi Aggarwal, Alec Brandon, Ariel Goldszmidt, Justin Holz, John A. List, Ian Muir, Gregory Sun, and Thomas Yu

Prior research on racial profiling has found that in encounters with law enforcement, minorities are punished more severely than white civilians. Less is known about the causes of these encounters and their implications for our understanding of racial profiling. Using high-frequency location data of rideshare drivers inFlorida (N = 222,838 individuals), we estimate the effect of driver race on citations and fines for speeding using 19.3 million location pings. Compared with a white driver traveling the same speed, we find that racial or ethnic minority drivers are 24 to 33% more likely to be cited for speeding and pay 23 to 34% more money in fines. We find no evidence that accident and reoffense rates explain these estimates, which suggests that animus against minorities underlies our results

Science, Volume 387, Issue 6741Mar 2025, 5p,

By Thalia González

The ever-growing list of names of Black victims who have died at the hands of police has emboldened a new public narrative that frames police violence—and other more commonplace, though less lethal, disparate policing practices—as a public health crisis rooted in this country’s history of racism and anti-Blackness. This public narrative in turn has spawned a diverse set of responsive actions in both the public and private sectors directed at addressing the effects of individual and structural racism on health. Yet missing from this linkage between police violence and racialized health disparities is any focus on the educational system, despite the increasing prevalence of police and standard policing practices in K-12 schools and the clear racial disparities of school policing. The central claim of this Essay is that school policing is an obvious public health issue. It sits at the nexus of two critical social determinants of health—education and racism—and requires targeted attention as such. The racialized nature of school-policing practices and the disparate outcomes for Black students are well documented. And, by applying a public health lens to this school police literature, specific individual- and aggregate-level health and mental outcomes become apparent. School policing negatively affects Black students’ mental health and physical safety, diminishes protective health factors, and places students at heightened risk for justice-system entry. Finally, understanding school policing as a public health issue has significant potential benefits and practical implications, especially for the antiracist health-equity movement.

Stanford Law Review Online, Vol. 73, 2021. 14p.

By Lucy Strang, Jack Cattell, Eddie Kane, Emma Disley, Brenda Gonzalez-Ginocchio, Alex Hetherington, Sophia Hasapopoulos, Emma Zürcher  

Background to the Report RAND Europe, in partnership with Get the Data and Skills for Justice, was commissioned by the Ministry of Justice in 2021 to conduct a study funded by the Shared Outcomes Fund on how police in England and Wales use options to resolve cases out of court to support adults (aged 18 or over) with health-related vulnerabilities.1 Following legislative reforms, a ‘two-tier plus’ framework for Out of Court Disposals (OOCDs; or Out of Court Resolutions2) is due to come into force nationally. This new framework consolidates the current statutory disposals into two primary options: Diversionary Caution and Community Caution. In advance of the implementation of the framework, this study aimed to provide an overview of how different police forces use OOCDs; to improve the use of OOCDs with conditions attached that address mental health and other health-related vulnerabilities; and to produce the foundations of practice change and improve the data collection methods to monitor their use and enable potential further research to explore their effectiveness. The study took place in three phases: • In Phase 1, the research team captured the current use of OOCD conditions to support adults with health vulnerabilities and relevant services available locally for each of the 37 police force areas in England and Wales participating in this study, including identifying any local gaps in service provision. • In Phase 2, the research team explored in greater depth how health vulnerabilities are identified, relevant conditions set, and progress is monitored, as well as perceptions of the effectiveness of the conditions set in a sample of seven police forces. • In Phase 3, the research team worked with seven3 police forces on a more detailed follow-up to co-produce the foundations of practice change, developing improved operational practice around the use of OOCDs, and creating supportive guidance, tools and training to enable effective application of OOCDs with health related conditions. In addition, the research team worked with these forces to improve data collection on the use of OOCDs with conditions attached to enable potential longer-term analytical work to isolate the short, medium- and long-term impacts of individual interventions on reoffending. This Report presents findings from all three Phases of this study. It is intended to be useful and relevant for frontline and operational police officers, service providers and policy stakeholders. 1.2 Key findings from this study Force-level approaches to OOCDs • Just over half (19) of the participating forces were using a two-tier OOCD model in March 2022, with a further 13 forces reported to be introducing two-tier in 2022 or working towards introducing it in 2023. • The OOCD processes and protocols used varied a great deal between forces and work with the case study forces identified significant missed OOCD opportunities, even in forces which had high levels of OOCD usage. • Across 37 forces, 189 services were identified that could be attached as conditions to OOCDs, with substance misuse and mental health services the most commonly available to be attached to OOCDs. • Nevertheless, most force areas reported that the local provision of mental health-related services generally was not sufficient for the needs of vulnerable offenders with OOCDs. • A range of funding models for available services were identified, the most common of which were police-funded, externally funded (for example, by local authorities) and offender-funded. • Of the forces that reported engaging with service providers as part of their OOCD process, relationships with service providers were generally maintained through some form of regular contact. • The training of police officers and staff on OOCDs, particularly in relation to conducting vulnerability assessments, was generally conducted on an ad hoc basis and was not available as a structured programme for most police forces, with staff turnover and inexperienced officers identified as key challenges. • Disproportionality in who received OOCDs was identified as a concern by some OOCD stakeholders. • Force use of OOCD scrutiny panels, which independently review anonymised cases, varied greatly across forces. Frontline approaches to OOCDs • Three levels of decision-makers at key OOCD decision gateways – the officer in charge (OIC), their supervisor and the force OOCD management and support functions – were identified. • Most police forces did not have a force-wide policy requiring a health vulnerability screening and assessment during the OOCD decision-making process and the use of a tool to assess health vulnerabilities was a well established process in only a minority of forces, usually those with a dedicated OOCD team. • The majority of forces were still reliant on frontline officers and their supervisors to make decisions regarding OOCD condition setting and deciding on any supportive interventions. • The most effective OOCD management processes and outcomes were found in those with a dedicated team. • The responsibility for monitoring compliance varied significantly between forces, with some assigning it, for example, to a dedicated OOCD team, and others to the OIC or an OOCD caseworker. 5 experiment and process evaluation would offer the most rigorous findings in the current context. 1.3 Reflections and implications Overall, findings from the study indicate that there is significant variation across forces in England and Wales in their OOCD processes and in how well-developed and well-established these processes are. At the force level, it appeared that OOCDs were underused in many forces; across the 31 forces that shared information on outcomes given to offenders in 2021, on average only 8% of all offenders were given an OOCD, but this varied substantially between forces. Furthermore, significant gaps were identified across most force areas in the availability of interventions to meet the needs of vulnerable offenders. Furthermore, limited provision of training on OOCD use, staff turnover, high proportions of inexperienced officers, and the disproportionality in who receives OOCDs were identified as significant force-level challenges to making the best use of OOCDs to support adults with health vulnerabilities. At the frontline operational level, limited use of vulnerability assessments in the OOCD process and limited input from Liaison and Diversion (L&D) services were also widely reported. In relation to offender engagement and compliance with conditions, there is a lack of meaningful data available which creates challenges in understanding the effectiveness of their use. Overall, the existence of a dedicated OOCD team or independent entity was associated with strong and consistently applied OOCD processes. While most interventions identified in this study have not been rigorously evaluated, broader evidence from the UK and abroad suggests that OOCDs can address health vulnerabilities and reduce reoffending. In Section 5, we discuss how relevant data can be collated to facilitate the management, monitoring, and evaluation of OOCDs. Based on these reflections, our Phase 3 work produced a series of practice guides and tools to support forces to develop and maintain good practice in using OOCDs to support adults with health vulnerabilities. These guides and tools, listed below, are referred and linked to where appropriate throughout this report.    • Health Vulnerability Assessment Guide: to support forces in identifying the health vulnerability assessment process and enabling better decision-making throughout. This guide also includes good practice examples for working with Liaison and Diversion. • Quality Assurance Guide: discussing how forces can procure in a way that facilitates a good evidence base. • Auditing Missed Opportunities Guide: provides forces with a simple methodology for auditing OOCD decisions to identify learning. • Data collection tool prototype: to support forces in gathering and using OOCD data. In addition, the study team developed OOCD training resources for forces to support relevant officers and decision makers on setting conditions to OOCDs to address health vulnerabilities, and to support higher level decision makers on implementing OOCD processes. Implications Sections 3, 4 and 5 conclude with a series of implications for OOCD practitioners and stakeholders in light of the implementation of the statutory two-tier plus framework in 2023. At the force level (Section 3), these implications are: • Each force should review their current processes and protocols to ensure significant opportunities to use OOCDs for those with health vulnerabilities are not being missed. This could include offence type audits and more detailed scrutiny of cases given OOCD and equivalent cases where they were not. A guide developed as part of this study is available (see the Rand website). • Forces should analyse data on local needs to identify any gaps in service provision, and work with service providers to address these gaps. • Forces should build service provision for OOCDs and their relationships with service providers by piloting and scaling up services in response to identified local need (and informed by robust evidence of effectiveness – see Section 5 below (see the Rand website). • Where possible, forces should seek to identify and utilise service providers with stable sources of funding to help ensure resilience in service provision. This may mean that some services are funded by the police to provide this stability. Furthermore, reducing offender-pays services can remove some barriers to compliance. • Forces should establish consistent and standardised modes of communication with service providers, including on compliance with and breaches of conditions. This may be easier with a dedicated OOCD team. • Forces should facilitate good information sharing by integrating service providers into police IT systems (in compliance with relevant data protection regulations.) • Each force should review their current training arrangements to ensure all those involved in OOCD decision-making are suitably trained in this area. Forces can consider adopting/adapting the training model outlined in this guidance (see the Rand website). • Each force should review its current use of OOCD attached services aimed at those with health vulnerabilities to ensure that their current practice is not resulting in disproportionality in the use of OOCDs or discriminating against some individuals, groups or communities. • Each force should review their current adult OOCD scrutiny arrangements to ensure that their overall oversight and accountability mechanisms for OOCDs are more consistent and comprehensive, as well as able to address wider issues of disproportionality. At the frontline operational level (Section 4), these implications are: • Each force (where not already in place) should review its position on having a dedicated OOCD team and develop options to put one in place. • Each force should review their current approach to screening for and assessing health vulnerabilities as part of the OOCD decision making process including links to L&D or equivalent services in all relevant settings including for Voluntary Attendance. The research team has developed a guide on working with L&D for OOCDs (see the Rand website).  ....continued.....

London: UK Ministry of Justice, 2024. 150p.

By Brian A. Jackson, Pauline Moore, Jennifer T. Leschitz, Benjamin Boudreaux, Jo Caulkins, Shoshana R. Shelton

Violence by K–12 students is disturbingly common. Ensuring that schools have effective ways to identify and prevent such incidents is becoming increasingly important. Various concerning behaviors or disturbing communications, including direct threats, can precede acts of violence. Although removing every student exhibiting such behaviors might seem prudent, doing so can be counterproductive, limiting the effectiveness of safety efforts. With effective systems for behavioral threat assessment and management (BTAM), schools can assess and respond to concerning behavior to protect the community and respond to the student whose behavior caused concern.

To do so, schools need the tools to respond. Tools may include restrictive measures or law enforcement involvement in the most serious cases, but other options can be more effective. Those additional options include different types of mental health intervention, counseling, and other supports. Teams with extensive tools available to them can better customize interventions, increasing the chance of positive outcomes for all involved.

In this report, the authors draw on published literature and extensive interviews with education and public safety practitioners to build an inventory of the many intervention options that are valuable for schools in the management phase of BTAM. In addition, drawing on varied approaches from the fields of counseling, school discipline and behavioral management, and other professions that must match appropriate services to the needs of youth in their care, the report discusses decision support tools to help management teams implement this critical part of efforts in preventing targeted violence and keeping school communities safe.

Key Findings

Various Intervention Options Are Available for K–12 BTAM Efforts

Support-focused interventions can address the underlying causes of problematic student behavior and also lead a student toward a more favorable, positive path into the future.

By using supportive counseling and other interventions, BTAM is widening the options available for school leaders and staff to address problematic behavior that has the potential to develop into violence.

To be effective, school BTAM teams need a broad set of tools, including options appropriately matched (1) to the specifics of a student's problematic behaviors, (2) to the unique school community and environment, and (3) to the needs and circumstances of the student or students involved.

Insights from Education, Public Safety, and Other Fields Can Be Combined to Support Matching Effective Interventions to Student Needs

Decision support tools and resource-matching guidance can help ensure that school-based teams are collecting the information required to taking a holistic approach to address a student's varied needs and help promote appropriate consistency to ensure that disparities in how BTAM teams respond do not substantiate concerns that BTAM processes are unfair or inequitable.

Using structured systems to capture data when a BTAM team (1) interviews students involved in an incident, (2) collects school or law enforcement data, or (3) contacts others for information about a student of concern provides a more straightforward starting point for selecting among multiple intervention options.

Recommendations

To better inform intervention planning, intervention tools should be designed so that they prioritize collecting data on factors that can be changed because pieces of information in BTAM that may be a useful part of assessing the danger posed by an individual may be useless for intervention planning.

The inventory of intervention options developed in this study could provide a starting point for schools to make conscious decisions as they (1) review the options available to their teams and (2) identify any options they do not have access to but that could become valuable near-term priorities to strengthen their school safety efforts.

Progress monitoring data of BTAM efforts can help better support students while also helping schools become more responsive to external oversight of their BTAM programs and allay concerns about the fairness and equity of outcomes across different student populations.

Including positive mileposts into threat management planning not only could help lay out a path to full completion of all intervention activities but could also help define goals more specifically for an at-risk student, motivating even more beneficial outcomes.

Santa Monica, CA: RAND, 2025. 170p.

By The Virginia Department of Criminal Justice Services

The Community Policing Act of 2020 (HB 1250; “the Act") mandated that the Virginia State Police (VSP) and other state and local law enforcement agencies, including police departments (PDs) and sheriff’s offices (SOs), begin collecting and reporting data on traffic stops as of July 1, 2020. State law enforcement agencies, PDs, and SOs are required to collect data on the race, ethnicity, and other characteristics of the drivers stopped, and on other circumstances of the stop such as the reason for the stop, whether any individuals or vehicles were searched, and the outcome of the stop (arrest, citation, warning, etc.). All reporting agencies are to submit this data to VSP, who maintain the data in the Community Policing Database.

The Act also mandated that the Virginia Department of Criminal Justice Services (DCJS) periodically obtain data from the Community Policing Database and produce an annual report “for the purposes of analyzing the data to determine the existence and prevalence of the practice of bias-based profiling and the prevalence of complaints alleging the use of excessive force." Such reports shall be produced and published by July 1 of each year.

This is the third of these reports from DCJS. It contains a review of how the data was collected and analyzed as well as preliminary findings of data from 650,387 traffic stops reported in Virginia during the nine-month period between July 1, 2022, and March 31, 2023. This report also presents the findings from analyses of statewide data; aggregated data from the seven VSP Divisions; and data from each individual law enforcement agency that reported sufficient data to the Community Policing Database.

The information presented in this report is preliminary and should be interpreted with caution. Although this analysis identified disparities in traffic stop rates related to race/ethnicity, it does not allow us to determine or measure specific reasons for these disparities. Most importantly for this study, this analysis does not allow us to determine the extent to which these disparities may or may not be due to bias-based profiling or to other factors that can vary depending on race or ethnicity. These other factors include differences in locations where police focus their patrol activities, differences in underlying regional populations, differences in driving patterns among individuals, and the lack of a scientifically established baseline for determining the number of drivers in each racial/ethnic group who are on the road and subject to being stopped while driving.

The analysis of racial disparity is a complex field with a vast array of potential contributing factors. Many data elements could play influential roles in racial/ethnic patterns of traffic enforcement but are unavailable to DCJS. Factors like the race of the officer performing the stop, agency policies and community priorities driving enforcement patterns, police report narratives outlining legal justifications for stop, search, and arrest can all inform stop patterns but are not within the current purview of available Community Policing Act data. Additionally, the data presented in this report cannot reflect any stop trends from agencies which did not provide data or records that were excluded for completeness issues. As such, while the report presents stop, search, and arrest disparities based on the available data, they should not be construed as complete and final proof of disparity OR any explanation of contributing factors which drive genuine disparities which may exist.

This report does not tabulate the many positive actions that can occur for a traffic stop such as seizures of guns, confiscation of drugs, and ensuring valid and current drivers’ licenses. The Community Policing Act imposes narrow requirements for data collection and analysis, and any benefits of traffic or pedestrian stops are not within the scope of the law.

While DCJS and VSP have introduced process improvements based on lessons learned in past reporting, the Community Policing Act is still in the early stages of implementation. More and better data, as noted in the recommendations, is needed to make the observations in this report more than directional, and the costs of such data gathering need further evaluation. As the report notes, many PDs and SOs − especially smaller agencies with limited resources − continue to face challenges establishing the data collection and reporting required under the Act. The majority of local law enforcement agencies (LEAs) in Virginia (255, or 74%) employ 50 or fewer sworn officers, including 118 (or 34%) employing 10 or fewer sworn officers. Many of these agencies have faced challenges fulfilling all requirements imposed by the Act and aligning their collection practices with the changes introduced since first implementation of the Act. For this reason, some agencies were unable to report complete data responsive to the Community Policing Act for the entire year, and in some cases the quality of the data was limited. Additionally, a substantial number of smaller agencies reported so few traffic stops that it was not possible to interpret data related to driver race/ethnicity. The state may wish to consider providing additional resources to LEAs, particularly smaller agencies, to support their ability to comply with the data-related provisions of the Act.

Another important limitation to the data and findings presented in this report relates to the race/ethnicity data in the Community Policing Database itself. Because the state lacks a standardized mechanism for reporting the race or ethnicity of a given driver, law enforcement officers must either make their own determination about a driver’s race/ethnicity (which may or may not be accurate) or ask for that information in the course of the traffic stop, which could raise constitutional concerns or escalate the perception of conflict in certain situations. Virginia does not collect and store information about a driver’s race/ethnicity, whether in driver-related databases maintained by the Virginia Department of Motor Vehicles or on individual driver’s licenses. Whether and to what extent the data related to driver race/ethnicity in the Community Policing Database accurately captures this information cannot be determined without further review.

The factors described above limited the ability of DCJS staff to conduct any complex statistical analysis of the data or to draw any firm conclusions about the existence and prevalence of the practice of bias-based profiling in a given agency or jurisdiction. It is anticipated that the reporting, analysis, and interpretation of Community Policing Act data will improve in the future as the program matures.

Richmond: Virginia Department of Criminal Justice Services, 2021. 73p.

By Stephanie Seguino, Nancy Brooks, Pat Autilio

This study has three goals. The first it to analyze police behavior as regards race and traffic policing. The second is to evaluate police compliance with the law requiring the collection and reporting of traffic stop data. And the third is to evaluate the effectiveness of the legislation in generating robust data collection on race and traffic policing that is relatively user friendly for analysis by community stakeholders. With regard to the first goal, we examine the data for evidence of racial disparities in several areas: racial shares and magnitudes of stops as well as racial disparities in stop rates, reasons for stops, arrest rates, search rates, and contraband “hit” rates. We also examine trends to determine whether racial disparities fall over time, particularly in response to the legalization of cannabis in July 2018. Our study is based on more than 800,000 traffic stops and 79 Vermont law enforcement agencies. The study includes a number of agencies that had not reported their data in time for our earlier study (Seguino and Brooks 2017). In addition to providing a statewide overview of racial disparities, we compare policing patterns as well as racial disparities across agencies, and separately for municipal law enforcement agencies, sheriff’s departments, and the Vermont State Police. We report raw data on all agencies in our sample, and these results can be found in the appendix. We have been careful to include in the body of the report that follows agency-level statistics only for those agencies that have the minimum number of observations by race (typically, 10 or more). Our main findings are as follows: • The Black and Hispanic shares of stopped drivers exceed their shares of the estimated driving population. The data indicate Black drivers were over-stopped by between 3% to 81%, depending on the measure of the driving population used. Hispanic drivers were over-stopped by 26%. The shares of stops of all other racial groups are at or below their share of the driving population. These numbers represent a statewide average, and obscure wide variation at the agency level. We provide detailed agency-level data in the report, which show that approximately 45 agencies over-stopped Black drivers by more than 25%. • The stop rate per 1,000 residents is very high in Vermont (255 drivers stopped per 1,000 residents) compared to the national average of 86 per 1,000 residents. This overall average obscures notable racial disparities in stop rates. The statewide white stop rate per 1,000 white residents is 256 compared to 459 stops of Black drivers per 1,000 Black residents. The Black stop rate is about 80% higher than the white stop rate and matches the upper bound described above since one of our measures of the driving population of an area is its number of residents. • These averages also obscure the wide variation in stop rates per 1,000 residents. Of particular concern are agencies with large racial disparities in stop rates that also significantly over-stop relative to the national average. For example, in Bennington the overall stop rate per 1,000 residents is estimated to be 659 and Black drivers are over-stopped from 55% to 335% depending on the measure of driving population. • Black and Hispanic drivers were ticketed at a higher rate than white drivers, and Black drivers were also more likely to be given multiple tickets per stop. Our ability to report accurately on ticket rates is limited by data quality concerns as some agencies only report a single outcome per stop even when more than one outcome occurred, such as multiple tickets. • White drivers were more likely to be stopped for moving violations than Black drivers. Black drivers were more likely to experience a stop for vehicle equipment violations. We are concerned that this type of stop may be more investigatory and pretextual than moving violations. Stops that are investigatory/pretextual, based on suspicion of illegal activity rather than observable behavior or evidence, are more susceptible to officer racial bias than stops based on other reasons, such as a moving violation or suspicion of Driving While Impaired (DWI). Several experts have recommended banning this type of stop, which could help to reduce not only racial stop rate disparities but also search disparities. (A November 2019 ruling by the Oregon Supreme Court has banned this increasingly controversial policing practice). • The arrest rate of Black drivers is roughly 70% greater than that of white drivers. The Hispanic-white arrest rate disparity is even larger, with the arrest rate of Hispanic drivers 90% greater than the white arrest rate. Some agency-level disparities were much wider. In Brattleboro, Black drivers’ arrest rate is 400% greater than the white rate; in Colchester, 185% times greater. • Black drivers are about 3.5 times more likely to be searched subsequent to a stop than white drivers and Hispanic drivers are searched at a rate that is 3.9 times greater than that of white drivers. Asian drivers are less likely to be searched than white drivers. Again, some agencies exhibited much wider disparities than the state average. In Brattleboro, Black drivers are almost 9 times more likely to be searched than white drivers; in Shelburne, 4.4 times greater; in South Burlington; 3.9 times greater; in Vergennes, 3.8 times greater; in Burlington, 3.6 times greater; and in Rutland, 3.45 times greater. • Black, Hispanic, and Asian drivers were less likely to be found with contraband than white drivers. The lower hit rate (that is, the percentage of searches that yield contraband) of drivers of color is widely regarded as providing evidence the police rely on a lower bar of evidence to search drivers of color than white drivers, suggesting possible racial bias in the decision to search. In a second test (a logit analysis) for racial bias in searches, we find that the race of the driver continues to be strongly correlated with the officer’s decision to search a vehicle, even after controlling for other factors that may influence the officer’s decision to search a vehicle. • We find that searches based on reasonable suspicion (a lower threshold of evidence than probable cause) have lower hit rates for all racial groups. And, the gap between the (higher) white hit rates and (lower) hit rates for people of color increases. Just as with investigatory/pretextual stops, searches based on reasonable suspicion are more prone to racial bias. With regard to trends over time: • From 2015 to 2019, the number of traffic stops has increased for all racial groups. Sheriff’s Departments registered an 86.4% increase in traffic stops over this time period, compared to a statewide average for all agencies of 39.7%. • Racial disparities in the increase in number of traffic stops are notable. While stops of white drivers increased by 44.6% over this time period, Black stops increased 72.5%; Asian stops, 66.7%; and Hispanic stops, 120.3%. • The share of stops that are investigatory/pretextual, including vehicle equipment stops, increased for all racial groups, but increases were greatest for Black drivers—so much so that by 2019, about one third of all stops of Black drivers were included in this category, up from 23% in 2016. For Hispanics, the increases in the share of such stops was even greater, rising from 18.0% in 2015 to 27.5% in 2019. • Racial disparities in arrest rates have also widened since 2014. The widening gap is due to a decline in the white arrest rate from 2018 to 2019 rather than an increase in the Black arrest rate. • Search rates declined for all racial groups after cannabis legalization but by 2019, the Black search rate continued to be 3 times greater than the white rate. Legalization of cannabis, in other words, did not have a substantial impact on the Black-white search rate disparity. The Hispanic search rate disparity widened from 2018 to 2019 with Hispanic drivers 2.6 times more likely to be searched than white drivers by 2019. • Hit rates have decreased for searches that result in any outcome (warning, ticket, or arrest) but the arrest-worthy hit rate rose slightly from 20.3% to 24.9% from 2018 to 2019. As search rates have fallen, searches appear to be somewhat more productive with regard to those that lead to an arrest but are somewhat less productive overall. Increasing hit rates suggests greater efficiency in policing decisions regarding searches, and clearly, less negative impact on drivers for whom searches are often traumatic experiences. Regarding data quality, our main findings are: • Data quality has improved for some but not all agencies over time. There continues to be a lack of compliance with the legislation requiring race data collection during traffic stops. Missing data on all of the outcomes of a stop, when stops have more than one outcome, date and time of stop, and stops IDs also hinders analysis. • Particularly worrisome is the large number of stops missing race of driver, the main concern of traffic stop data collection. One way to put into perspective the quantity of missing data is to compare the share of stops missing race of driver to the percentage of stops that are of BIPOC drivers. Given the low percentages of people of color in Vermont, even a small amount of missing race data can distort results. For more than a dozen agencies, the percentage of stops missing race of driver is at least double the percentage of stops that are reported to be of BIPOC drivers. At a minimum, this leads to low quality data and the accuracy of results from those agencies. It also violates the spirit of the legislation requiring race data collection. • The legislation has not been sufficiently precise or comprehensive in delineating the data to be collected. Police chiefs have interpreted the meaning of various components of the legislation differently, and thus do not follow a uniform method of reporting data. Some categories of data that would be useful—and are already collected—were not stipulated in the legislation. Law enforcement agencies have as a result declined to share those data. These findings suggest the need to revise the legislation on traffic stop race data collection in order to insure complete data that is uniformly submitted so that it can be analyzed without excessive difficulty.    

Burlington, VT: University of Vermont, 2021. 159p.

By Robin Joy

Act 193 mandates that law enforcement agencies collect data on roadside stops for the purpose of evaluating racial disparities. The Act dictates agency data collection and any related conversation centers on agency behavior. The Act and the data collected do not focus on or reflect the stories told by Black, Indigenous and People of Color (BIPOC) as related to their contacts with law enforcement agencies. Because of Vermont’s rural nature, small populations, and policing strategies, we conclude that traffic stop and race data are not sufficient to inform policy makers and stakeholders. Rigorous qualitative research focused on the experiences of the BIPOC community which detects patterns and trends can distinguish structural issues within the criminal justice system. Agency data should be used as a supplement to that research. The purpose of the study was to test different methods of assessing racial disparities in traffic stops for their applicability for all Vermont law enforcement agencies. In short, we found that this was not possible. This report reviews the methodologies tested and the findings. On Measuring Disparities 1. We tested three peer reviewed methods for benchmarking the driving population: Commuting Hour populations, Resident Driver populations, and Crash Data benchmarking. All three failed in Vermont because of the state’s rural nature and small populations. The low volume of people of color makes it difficult for consistent analysis. It is not possible for one benchmarking standard to be applied to all law enforcement agencies in the state. 2. We can recommend the “Veil of Darkness” analysis as an effort to examine racial disparities. However, that analysis essentially measures one work shift in a police department. In some departments that may just be a single officer. 3. Post-stop outcome measures may be useful, however, without more information on the stop (such as the violation for which the person was ticketed/arrested and other circumstances surrounding the stop) it is of limited value. Further, because so few people are searched or arrested it is hard to draw a conclusion from the data. 4. Stop data will now include information as to how often the same person is stopped by a department. Specifically, the year, make, model, and color of the car and the town/state of residence and the state of the plate will be available. This will help illustrate the stories community members have spoken about in protests, legislative hearings, and news articles – stories of people who feel they are being continuously targeted. For example, using these additional data fields, researchers can identify a 30-year-old Asian female from Montpelier driving a 2008 White Honda CRV who has been stopped four times in one month for various reasons

Montpelier, VT: Crime Research Group, 2021, 27p. 

By The Crime Research Group

Act 193 mandates that law enforcement agencies collect data on roadside stops for the purpose of evaluating racial disparities. The Act dictates agency data collection and any related conversation centers on agency behavior. The Act and the data collected do not focus on or reflect the stories told by Black, Indigenous and People of Color (BIPOC) as related to their contacts with law enforcement agencies. Because of Vermont’s rural nature, small populations, and policing strategies, we conclude that traffic stop and race data are not sufficient to inform policy makers and stakeholders. Rigorous qualitative research focused on the experiences of the BIPOC community which detects patterns and trends can distinguish structural issues within the criminal justice system. Agency data should be used as a supplement to that research. Part 1 of this report covers the data collection process over the past five years. The purpose of Part 2, which is in a separate report, was to test different methods of assessing racial disparities in traffic stops for their applicability for all Vermont law enforcement agencies.

Montpelier VT: Crime Research Group, 2021. 12p.

By Robin Joy

Introduction

Criminal justice stakeholders and policymakers are interested in the way people with mental health concerns and/or substance use disorders engage with law enforcement agencies. This examination explores a sample of these interactions to describe individuals’ contact with the criminal justice system. A better understanding of these interactions can evaluate the utility of administrative data to inform policies regarding police responses in crisis incidents.

Methods

With data provided by a municipal police department, researchers identified 18 people who had the most arrests from 2018-2022 and at least one incident with a mental health flag in the Valcour system. Criminal histories were obtained and used in conjunction with data from the Vermont judiciary and Department of Corrections to construct a robust description of how these individuals interact with the criminal justice system.

This study is a preliminary exploration of the utility of administrative data in describing how and why people with behavioral health concerns utilize police services in one municipal police department. As such, the results may not be applicable to other agencies and populations in Vermont. The cohort was too small to find patterns in the criminal histories that suggest how a person goes from limited contact in the first two years to a high utilization of services. Missing also is how much contact the cohort had with law enforcement during their lifetime. Additionally, the interaction that individuals with behavioral health concerns have with other law enforcement agencies, social service providers, and hospitals was outside the scope of study.

Findings

On average, individuals in the cohort had 1.39 contacts per day with law enforcement. Most of the calls were related to non-violent matters. The most common type of call involved intoxication followed by trespass.

Montpelier VT: Crime Research Group, 2024. 18p.