Ripa Board Annual Report 2020

R ACIAL & I DENTITY P ROFILING ANNUAL REPORT A DVISORY 20 20 BOARD i RACIAL AND IDENTITY PROFILING ADVISORY (RIPA) BOARD SAHAR DURALI, Board Co-Chair, Associate Director of Litigation and Policy, Neighborhood Legal Services of Los Angeles; Appointed by the Attorney General of California (Board Co-Chair as of September 2019) SHERIFF DAVID ROBINSON, Board Co-Chair, Sheriff, Kings County Sheriff’s Office; Designee of the President of California State Sheriffs’ Association MICAH ALI, Vice President, Compton Unified School District Board of Trustees; Appointed by the President Pro Tempore of the Senate OSCAR BOBROW, Chief Deputy Public Defender, Solano County; Designee of the California Public Defenders Association PASTOR J. EDGAR BOYD, Pastor, First African Methodist Episcopal Church of Los Angeles (FAME); Appointed by the Attorney General of California SANDRA C. BROWN, Lieutenant (ret.), Palo Alto Police Department; Appointed by the President Pro Tempore of the Senate ANDREA GUERRERO, Executive Director, Alliance San Diego; Appointed by the Speaker of the Assembly (Board Co-Chair through September 2019) LAWANDA HAWKINS, Founder, Justice for Murdered Children; Appointed by the Governor of California DAMON KURTZ, Vice President, Peace Officers Research Association of California (PORAC); Designee of President of PORAC REVEREND BEN MCBRIDE, Co-Director, PICO California; Founder, Empower Initiative; Appointed by the Attorney General of California EDWARD MEDRANO, Chief, California Department of Justice, Division of Law Enforcement; Designee of the Attorney General of California DOUGLAS ODEN, Senior Litigation Attorney, Law Offices of Oden & Greene; Appointed by the Speaker of the Assembly STEVEN RAPHAEL, Professor of Public Policy, University of California, Berkeley; Appointed by the Governor of California TIMOTHY P. SILARD, President, Rosenberg Foundation; Appointed by the Attorney General of California COMMISSIONER WARREN STANLEY, Commissioner, California Highway Patrol; Designated by The Racial and Identity Profiling Act of 2015 CHIEF DAVID SWING, President, California Police Chiefs Association; Chief, Morgan Hill Police Department, Designated by The Racial and Identity Profiling Act of 2015 TIMOTHY WALKER, Senior, San Francisco State University; Mentor, Community Coalition, Los Angeles; Appointed by the Attorney General of California 1 The Racial and Identity Profiling Advisory (RIPA) Board thanks the following staff from the California Department of Justice for their assistance and contributions to this report: Editors California Department of Justice, Civil Rights Enforcement Section (CRES) Allison S. Elgart, Deputy Attorney General Catherine Z. Ysrael, Deputy Attorney General Domonique C. Alcaraz, Deputy Attorney General Anna Rick, Associate Governmental Program Analyst Aisha Martin-Walton, Retired Annuitant California Department of Justice, California Justice Information Services Division (CJIS) Kevin Walker, Research Associate I, Research Center Trent Simmons, Ph.D., Research Analyst II, Research Center Tiana Osborne, Research Analyst I, Research Center Evelyn Reynoso, Research Analyst I, Research Center Project Supervisors Nancy A. Beninati, Supervising Deputy Attorney General, CRES Randie C. Chance, Ph.D., Director, Research Center, CJIS Jenny Reich, Director, Justice Data and Investigative Services Bureau, CJIS Additional Editors and Contributors Amanda Burke, Ph.D., Research Associate I, Research Center Erin Choi, Program Manager, Client Services Program, CJIS Charles Hwu, Data Processing Manager, Application Development Bureau, CJIS Tiffany Jantz, Ph.D., Research Associate I, Research Center Tanya Koshy, Deputy Attorney General, CRES Audra Opdyke, Assistant Director, Justice Data and Investigative Services Bureau, CJIS Jannie Scott, Ph.D., Research Associate I, Research Center Christine Sun, Special Assistant to the Attorney General, Executive Office 2 The RIPA Board thanks former Associate Governmental Program Analyst Kelsey Geiser for her significant contributions and dedication to this initiative over the years. The RIPA Board thanks Alfred Palma from the California Department of Justice for his diligence and for serving as the travel coordinator to the Board. The RIPA Board thanks the Commission on Peace Officer Standards and Training (POST) for its partnership and looks forward to continuing to build on this collaboration. The RIPA Board thanks Magnus Lofstrom, Ph.D., Brandon Martin, MA, and Justin Goss, MPP, of The Public Policy Institute of California (PPIC). PPIC researchers provided technical research assistance but are not responsible for the accuracy of the raw source data and/or any conclusions extrapolated from the technical research assistance provided and contained in the RIPA report. The RIPA Board thanks Jack Glaser, Ph.D., Professor, Goldman School of Public Policy, University of California, Berkeley; and Emily Owens, Ph.D., Professor, Department of Criminology, Law and Society and Department of Economics, University of California, Irvine, for their assistance in preparing this year’s report. The RIPA Board appreciates the participation of community members, members of law enforcement, advocates, researchers, and other stakeholders. Public participation is essential to this process, and the RIPA Board thanks all Californians who have attended meetings, submitted letters, and otherwise engaged with the work of the Board. We look forward to continuing input from the public. 3 Table of Contents EXECUTIVE SUMMARY 5 OPENING LETTER FROM THE RIPA BOARD CO-CHAIRS 13 INTRODUCTION 15 ANALYSIS OF WAVE 1 STOP DATA: JULY 1, 2018 - DECEMBER 31, 2018 20 RACIAL AND IDENTITY PROFILING POLICIES AND ACCOUNTABILITY 43 CALLS FOR SERVICE AND BIAS BY PROXY 54 CIVILIAN COMPLAINTS: POLICIES AND DATA ANALYSES 58 REVIEW OF WAVE 1 AGENCY COMPLAINT FORMS 81 POST TRAINING RELATED TO RACIAL AND IDENTITY PROFILING 91 RELEVANT LEGISLATION ENACTED IN 2019 95 CONCLUSION 96 4 EXECUTIVE SUMMARY California’s Racial and Identity Profiling Advisory Board (Board) is pleased to release its Third Annual Report. The Board was created by the Racial and Identity Profiling Act of 2015 (RIPA) to shepherd data collection and provide public reports with the ultimate objective to eliminate racial and identity profiling and improve and understand diversity in law enforcement through training, education, and outreach. For the first time, the Board’s report includes an analysis of the stop data collected under RIPA, which requires nearly all California law enforcement agencies to submit demographic data on all detentions and searches. This report also provides recommendations that law enforcement can incorporate to enhance their policies, procedures, and trainings on topics that intersect with bias and racial and identity profiling. This report provides the Board’s recommendations for next steps for all stakeholders – advocacy groups, community members, law enforcement, and policymakers – who can collectively advance the goals of RIPA. In rendering these recommendations, the Board hopes to further carry out its mission to eliminate racial and identity profiling and improve law enforcement and community relations. Recommendations for Law Enforcement Agencies The Board has engaged in an extensive review of best practices to provide law enforcement with concrete recommendations focused on improving bias-free policing and civilian complaint policies and procedures. The Board recommends that law enforcement engage with their communities as they develop and improve policies and practices that are strong and effective while also enhancing transparency, building trust, and promoting the safety and, well-being of all parties. Below we provide an overview of the recommendations included in this year’s report, and we strongly encourage stakeholders to review the detailed policies set forth later in this report and in the attached Appendix. Policies: This report contains model language for the following: a clear, written bias-free policing policy; definitions related to bias; the limited circumstances when personal characteristics of an individual may be considered; training; data collection and analysis; encounters with the community; accountability and adherence to the policy; and supervisory review. The Board recommends that all agency personnel, both sworn and civilian, receive training on their bias-free policing policies. Agencies are further encouraged to develop policies and training on how to prevent bias by proxy when responding to a call for service. In addition to including model language, the Board conducted a policy review to assist Wave 1 agencies in identifying areas of opportunity to incorporate the best practices and model language presented in this report and the 2019 RIPA Annual Report. For the purposes of this report, Wave 1 agencies refers to the eight largest law enforcement agencies in the state that began collecting stop data on July 1, 2018, and reported it to the department on April 1, 2019. Civilian Complaints: Law enforcement agencies should evaluate their civilian complaint process and align their complaint forms, where practical, with the best practices laid out in this report. The Board conducted a review of the complaint forms of the Wave 1 agencies to identify areas of opportunity to adopt additional best practices. The report examines the civilian complaint data, including data on reported racial and identity profiling allegations submitted to the Department of Justice by all RIPA reporting agencies in 2018; the report then highlights the factors that impact the disparities in the number of reported complaints by each agency. 5 Recommendations for Community Members The 2020 Annual Report contains recommendations that advocates and community members can use to engage with law enforcement to improve policies, accountability, and enforcement measures. The Board hopes community members can take the model language and best practices delineated in the report to push law enforcement agencies to improve their policies and procedures. The Board also thanks members of the community for attending Board and subcommittee meetings and providing public comment. The Board hopes community members will continue to engage with the Board regarding its work. Recommendations for Policymakers The Board hopes the California Legislature and local governments can increase funding to law enforcement agencies to implement RIPA by supporting not only the data collection itself, but also in supporting law enforcement’s evaluation of the collected data as well as the development of anti-bias training and policies. To effectively fulfill their mandate under RIPA, law enforcement agencies must develop and further refine their data collection systems for stops, review and revise their policies and practices, and make other changes to personnel, supervision, and training. They cannot do so without additional funding and support. With respect to civilian complaints, the Board recommends that the Legislature amend Penal Code section 148.6 by striking the language imposing criminal sanctions for filing a false complaint. By doing so, the Board hopes to resolve a conflict between state and federal law, as well as remove cautionary language that is potentially chilling to the filing of a civilian complaint. Findings Regarding RIPA Stop Data • Between July 1, 2018 and December 31, 2018, the eight largest agencies in California, referred to as Wave 1 agencies in this report, collected data on vehicle and pedestrian stops. RIPA defines a stop as a detention and/or search by a peace officer. • Reporting agencies stopped over 1.8 million individuals during the stop data collection period. The California Highway Patrol conducted the most stops of all reporting agencies, which is unsurprising given the size and geographic jurisdiction of the agency and its primary mission with respect to highway safety. 6 Number of Stops by Agency 44,505, 3% 40,515, 2% 56,409, 3% California Highway Patrol 62,433, 3% Los Angeles Police Department 89,455, 5% Los Angeles County Sheriff’s Department San Diego Police Department 136,635, 8% San Bernardino County Sheriff’s 1,033,421, 57% Department 336,681, 19% San Francisco Police Department Riverside County Sheriff’s Department San Diego County Sheriff’s Department • 95.3 percent of stops were officer-initiated, while 4.7 percent of stops were in response to a call for service, radio call, or dispatch. 39.8% 33.2% 15.2% 5.5% 4.4% 1.2% 0.6% 0.2% • Individuals perceived to be Hispanic (39.8%), White (33.2%), or Black (15.2%) comprised the majority of stopped individuals. 7 deppotS fo tnecreP slaudividnI Hispanic White Black Asian Middle Eastern/South Asian Multiracial Pacific Islander Native American • The most commonly reported reason for a stop across all racial/ethnic groups was traffic violations, followed by reasonable suspicion. A higher percentage of Black individuals were stopped for reasonable suspicion than any other racial identity group. Asian Black Hispanic Middle Eastern/South Asian Multiracial Native American Pacific Islander White Total 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Traffic Violation Reasonable Suspicion Other • To provide context for the racial distribution of stopped individuals, the Board compared the distribution to two benchmark data sources: 1) the American Community Survey (ACS) and 2) the Statewide Integrated Traffic Records System (SWITRS). Black individuals represented a higher proportion of stopped individuals than their relative proportion of the population in both benchmark datasets. 2017 American Community Survey (ACS) 39.8%41.4% Stop Data ASC 33.2% 34.7% 15.1% 11.9% 6.3% 1.8% 5.5% 4.4% 3.0% 0.3% 0.3% 0.3% 1.2% 0.6% 0.2% 0.0% Hispanic White Black Asian Middle Multiracial Pacific Native Other Eastern/ Islander American South Asian Statewide Integrated Traffic Records System (SWITRS) Stop Data (Traffic Violations Only) SWITRS 40.0% 38.4% 33.6% 33.9% 13.4% 9.7% 9.3% 8.8% 6.1% 6.9% Hispanic White Black Asian Other 8 • The veil of darkness (VOD) method is a third benchmarking method used this year. The VOD analysis compares the proportion of individuals stopped during daylight hours to the proportion of individuals stopped when it is dark outside during the intertwilight period, i.e., the time of day that is dark during Standard Time, but light during Daylight Savings Time. Having a higher proportion of stops of individuals of a particular racial or ethnic group occur in the light, compared to White individuals, may be considered evidence of bias towards that group. The VOD analysis of this year’s data indicated disparities in stops during light hours vs. dark hours for some racial and ethnic identity groups. For example, individuals perceived to be Pacific Islander or Multiracial had a higher proportion of their stops occur during light hours than individuals perceived to be White. Inter-Twilight Stop Frequencies by Race/Ethnicity 100% 49.7% 48.8% 50.5% 49.5% 53.5% 54.5% 57.0% 50.0% Light 50% Dark 50.3% 51.2% 49.5% 50.5% 46.5% 45.5% 43.0% 50.0% 0% Asian Black Hispanic Middle Eastern/ Multiracial Native AmericanPacific Islander White (9,428) (25,045) (66,682) South Asian (2,170) (389) (931) (54,546) (8,333) • Overall, 9.9 percent of stopped individuals were subject to a person or property search. • Officers searched Black individuals at a rate 2.9 times the rate at which they searched White individuals (18.7% vs. 6.5%). • Middle Eastern/South Asian individuals had the lowest search rate (2.8%). Asian 96.9% 3.1% Black 81.3% 18.7% Hispanic 88.8% 11.2% Middle Eastern/South Asian 97.2% 2.8% Not Searched Multiracial 88.4% 11.6% Searched Native American 88.9% 11.1% Pacific Islander 92.1% 7.9% White 93.5% 6.5% Total 90.1% 9.9% • Search yield rate analyses showed that, when officers searched individuals, contraband or evidence was generally found on White individuals at higher rates than individuals from all other groups. 21.8% 22.5% 21.0% 22.4% 21.1% 24.3% 18.8% 19.3% Search Yield Rate 9 fo tnecreP dehcraeS slaudividnI Asian Black Hispanic Middle Eastern/South Asian Multiracial Native American Pacific Islander White • When examining search yield rates by the presumed level of discretion available to the officer in deciding to conduct a search, yield rates for racial/ethnic groups of color were lower than for White individuals for higher-discretion searches, i.e., searches for which the only basis for search was “consent given.” This was also true for most racial/ethnic groups of color when only examining lower discretion searches (searches in which the basis for search was incident to arrest, vehicle inventory, or search warrant), with the exception of Black and Multiracial individuals, who had higher yield rates than White individuals for lower discretion searches. • 60.3 percent of all individuals stopped were issued a citation and/or arrested. Native American and Black individuals had the highest arrest rates and the lowest rates of citation. Middle Eastern/South Asian and Asian individuals had the highest citation rates and the lowest arrest rates. 61.4% 57.6% 48.7% 45.9% 48.5% 49.4% 36.8% 38.0% 11.4% 15.2% 13.6% 13.5% 16.0% 13.9% 11.3% 7.0% Asian Black Hispanic Middle Multiracial Native Pacific White Eastern/South American Islander Asian 10 slaudividnI fo tnecreP Citations Arrests Findings Regarding Civilian Complaint Data There were 1,081 allegations of racial or identity profiling filed in 2018 with the 134 law enforcement agencies subject to RIPA. Of these, 78 percent of the complaints included allegations of racial or identity profiling. Total Racial and Identity Profiling Allegations Reported Religion, 15, 1% Nationality, 37, 4% Gender, 51, 5% Age, 21, 2% Gender Identity Expression, 25, 2% Mental Disability, 30, 3% Sexual Orientation, 24, 2% Physical Disability , 34, 3% Race and Ethnicity, 844, 78% The following table shows the total number of civilian complaints reported in 2018 by Wave 1 agencies, the number of allegations of racial or identity profiling, and the number of sworn personnel each agency employed in 2018. There were notable disparities in the total complaints and racial and identity profiling allegations reported by agency. The reasons for these disparities likely include: 1) lack of uniformity regarding what constitutes a “civilian complaint” and how to quantify and document complaints; 2) lack of uniformity regarding how to process civilian complaints; 3) varying accessibility and knowledge of an agency’s complaint process; 4) disparate accessibility for people with disabilities; and 5) the potential deterrent impact of Penal Code section 148.6. 11 Wave 1 Agency Complaints Reported and Number of Sworn Personnel Employed in 2018 Agency Total Profiling Sworn Personnel Complaints Complaints Reported Reported Los Angeles Police 1,907 274 9,974 Department (14%) Los Angeles County Sheriff’s 986 67 9,426 Department (6.7%) California Highway Patrol 287 35 7,286 (12%) San Diego County Sheriff’s 9 1 2,572 Department (11%) San Francisco Police 678 21 2,306 Department (3%) San Bernardino County 104 35 2,018 Sheriff’s Department (33%) Riverside County Sheriff’s 46 4 1,795 Department (9%) San Diego Police Department 74 15 1,731 (20%) 12 Opening Letter from RIPA Board Co-Chairs Last year marked a major milestone for the Racial and Identity Profiling Act of 2015 (RIPA), the Racial and Identity Profiling Advisory Board (Board), and the State of California. In 2019, the California Department of Justice (Department) received its first set of stop data from the eight largest law enforcement agencies in the state (Wave 1 agencies). The Board has analyzed this data and incorporated the results into this year’s report. Specifically, the Board reviewed comprehensive demographic data on all stops and searches reported by the California Highway Patrol, Los Angeles Police Department, Los Angeles County Sheriff’s Department, Riverside County Sheriff's Department, San Bernardino County Sheriff's Department, San Diego County Sheriff's Department, San Diego Police Department, and San Francisco Police Department. This first wave of data documented approximately 1.8 million police detentions and searches across California. This is only the beginning. All California law enforcement agencies will begin reporting data on a rolling basis through 2023, generating public data on statewide stops and searches on an unprecedented scale. To understand the momentousness of this accomplishment, we must reflect on how this began and the work ahead needed to eliminate racial and identity profiling. In 2015, the California Legislature passed RIPA, groundbreaking legislation that requires all law enforcement agencies statewide to uniformly collect and report demographic data on all police stops and searches. RIPA also mandated the creation of the Board, with the bold intention of eliminating racial and identity profiling in policing. In 2016, its inaugural year, the Board made recommendations to the Attorney General’s Office on its drafting of regulations to implement RIPA. Under this stop data program, reporting officers must collect data on the reason for each detention or search, as well as detailed demographic data, including the perceived race or ethnicity, gender, age, LGBT identity, disability, and limited English fluency of the person detained or searched. Since its inception, the Board has engaged in a thorough study and examination of several civilian- facing aspects of law enforcement that relate to racial and identity profiling, including law enforcement training, civilian complaint processes, policies regarding racial and identity profiling and accountability, and policies regarding calls for service. In this year’s report as well as in previous ones, the Board has compiled comprehensive, evidence-based best practice recommendations and model policies. Now that RIPA and the Board have been in effect for four years, what does the future hold and what are the next steps? The Board urges all law enforcement agencies to compare their own policies to the best practice recommendations offered by the Board. However, the Board’s recommendations are only a starting point; we encourage agencies to think about how they can strive to go beyond the Board’s recommendations. We urge law enforcement agencies to work with and engage their home communities to develop policies and practices that advance equity and root out bias and harmful practices of racial profiling in all aspects of operations. Additionally, we urge law enforcement, advocates, and community members to reflect on and make use of the stop data reported for their home communities. We are hopeful that the stop data can serve as a starting point for meaningful collaboration and change, and look forward to supporting the community and law enforcement agencies in these endeavors. 13 We also strongly support increased funding for the implementation of RIPA. To date, the Board is unaware of any state funding allocated to local law enforcement agencies to implement these sweeping changes. The future will depend on fully funding the implementation of this important legislation which left unfunded, may soon hinder much of the work. Many agencies, especially small ones, are struggling from the lack of sufficient funding. We cannot let this legislation fail. Funding for this legislation must be a priority to ensure that this important work is done right. Finally, we extend our sincere appreciation and gratitude to everyone who has been on this journey with the Board throughout the last several years. The work of the Board to help identify and eliminate racial and identity profiling cannot be done without the continued engagement of the community and the commitment of law enforcement. We would especially like to recognize members of the public, particularly individuals who have shared their experiences of racial profiling, who have been indispensable participants in the Board’s work. We thank you for sharing your expertise, your time, your stories, and your pain with us over the years. We also thank law enforcement agencies around the state for embracing RIPA, sharing your implementation of this law, and ensuring complete and comprehensive data collection and reporting. We know this was no small feat and look forward to continued partnership with you in coming years. -Co-Chairs Sahar Durali and David Robinson 14 Introduction The Racial and Identity Profiling Act of 2015 (RIPA) created the Racial and Identity Profiling Advisory Board (Board), which is tasked with the ambitious charge of improving racial and identity sensitivity in law enforcement with the hope of eliminating bias in policing.1 The Board is composed of 19 members representing a wide range of sectors and expertise, including civil and human rights, law enforcement, and academia. The Board’s work is enhanced by the diverse perspectives and backgrounds of its members, as well as by the vibrant discourse brought to Board and subcommittee meetings by advocates, individuals impacted by racial profiling issues, members of the law enforcement community, and members of the public at large. Together, the Board and its stakeholders share the common goals of improving law enforcement-community relations, building trust, making policing more equitable, and striving to make all Californians feel respected and safe. These goals can be achieved through collaboration, transparency, and accountability. Background Since its inception, the Board has engaged with diverse stakeholders who share the goal of eliminating racial and identity profiling. The Board has heard from the community at Board and subcommittee meetings, consulted with the Department, and collaborated with the Commission on Peace Officer Standards and Training (POST) on its trainings related to racial and identity profiling. The Board also produced and released two annual reports describing the ongoing efforts to assess and prevent racial and identity profiling in California. These annual reports give the Board an opportunity to share detailed findings on the impact that race and identity may have in shaping law enforcement activities in California, as well as identifying best practices and policy recommendations to identify and eliminate racial and identity profiling.2 To that end, RIPA requires each annual report to include: • An analysis of law enforcement data regarding stops made by officers and civilian complaints; • An analysis of law enforcement training on racial and identity differences discussed in Penal Code section 13519.4; • A review and analysis of racial and identity profiling policies and practices across geographic areas in California; and • Evidence-based research on intentional and implicit biases that affect law enforcement stop, search, and seizure tactics.3 1 Pen. Code, § 13519.4, subd. (j)(1). 2 Pen. Code, § 13519.4, subd. (j)(3)(E). 3 Pen. Code, § 13519.4, subd. (j)(3). 15 RIPA also requires POST to consult with the Board in developing its trainings on racial and identity differences to better educate law enforcement about unlawful profiling and bias. In addition, RIPA mandates that:4 • The majority of California’s law enforcement agencies (LEAs) collect information on stops made by their officers, and report this information to the Department; RIPA also tasked the Department with writing the regulations to implement this data collection, in consultation with the Board and other stakeholders;5 • The stop data collected be made publicly available, except for the personal information of the person stopped and the unique identifying information of the reporting officer, which shall be protected from disclosure; and • Several changes to the civilian complaint data be reported to and published by the Department.6 Type of Data Collected for Each Stop The data collected about each stop includes three categories of information: 1) information about the stop itself, 2) information perceived by the officer about the person stopped, and 3) information about the officer making the stop. Table 1, below, spells out in more detail the information the officer must report in each of those three categories.7 Table 1: Officer Reporting Requirements Information Regarding Stop 1. Date, Time, and Duration 2. Location 3. Reason for Stop 4. Was Stop in Response to Call for Service? 5. Actions Taken During Stop 6. Contraband or Evidence Discovered 7. Property Seized 8. Result of Stop 4 Assem. Bill No. 1518 (2017-2018 Reg. Sess.) § 1-2. 5 Gov. Code, § 12525.2, subds. (a), (e). 6 Pen. Code, § 13012. 7 For more information on the specific data collected, please see State of California Department of Justice Office of the Attorney General. (2017). AB 953: Template Based on the Final Regulations. Available at https://oag.ca.gov/sites/all/files/agweb/pdfs/ripa/regs-template.pdf. 16 Information Regarding Officer’s Perception of Person Stopped 1. Perceived Race or Ethnicity 2. Perceived Age 3. Perceived Gender 4. Perceived to be LGBT 5. Limited or No English Fluency 6. Perceived or Known Disability Information Regarding Officer 1. Officer’s Identification Number 2. Years of Experience 3. Type of Assignment When reporting this information for each stop, the reporting officer selects from a standardized list of responses. These drop-down menus streamline the reporting process and, importantly, ensure that the data that is collected is uniform across all agencies. Separate from and in addition to these drop- down menus, officers are further required to complete an explanatory field (of no more than 250 characters) providing in their own words the Reason for Stop and Basis for the Search (if one is conducted). Methods of Submitting Data to the Statewide Repository In the spirit of facilitating a large and diverse array of individual law enforcement agencies to successfully implement the stop data requirements, the size of an agency determines when it is required to begin collecting and submitting data to the Department. Stop data collection for the eight largest agencies in the state began on July 1, 2018. These agencies have informally been termed the "Wave 1" agencies due to the rolling nature of the stop data collection time line. Accordingly, the next set of agencies to begin data collection are thus termed "Wave 2" and so on until the final group, "Wave 4" begins collecting the data (Table 2). Additionally, the data submission regulations provide agencies with three methods to submit data. These three methods of submitting data to the statewide repository are: 1) a DOJ-hosted Web Application, 2) Web Services, and 3) Secure File Transfer Protocol. The Department developed these three submission methods to provide flexibility to meet the needs of an agency’s local infrastructure. Importantly, the data standards for each of these methods are the same; each method utilizes standard fields and validation checks, which will be discussed in the next section of this chapter. Table 3 details the submission methods that Wave 1 agencies are currently using. 17 Table 2: Collection and Reporting Deadlines by “Wave” Reporting Size of Agency Data Collection Data Must be Approximate Wave Begins Reported to DOJ Number of Agencies 1 1,000+ July 1, 2018 April 1, 2019 8 2 667-999 Jan. 1, 2019 April 1, 2020 7 3 334-666 Jan. 1, 2021 April 1, 2022 10 4 1-333 Jan. 1, 2022 April 1, 2023 400+ Table 3: Wave 1 Agency Submission Methods Agency Type of Data Submission California Highway Patrol Web Services Los Angeles Police Department Secure File Transfer Protocol Los Angeles Sheriff’s Office Web Services Riverside Sheriff’s Office Secure File Transfer Protocol* San Bernardino Sheriff’s Office Web Services* San Diego Police Department Web Services* San Diego Sheriff’s Office Web Services* San Francisco Police Department DOJ-hosted Web Application *These agencies are using a locally installed copy of an application developed by the San Diego Sheriff’s Office and submitting data to the Department through Web Services or Secure File Transfer Protocol. All records submitted to the Department are stored in a statewide repository called the Stop Data Collection System (SDCS). The SDCS uses a series of rules and user permissions to protect the quality and integrity of the data. Some of these rules are listed below. • Reported data must be complete and must follow uniform standards. 18 • Access to stop records is restricted. • A specified error resolution process must be followed. • Once submitted, perception data (i.e., perceived demographic data about the person stopped) is locked and cannot be changed by the officer or agency. • Transactions are stored in system audit logs. 19 Analysis of Wave 1 Stop Data: July 1, 2018 – December 31, 2018 In the first wave of reporting (Wave 1), the eight largest law enforcement agencies in California collected data about stops conducted from July 1, 2018 to December 31, 2018. Officers collected data on over 1.8 million stops. RIPA defines stops as a detention and/or search of an individual. The records include data on the demographic information of the stopped individuals as perceived by the officer.8 The demographic information includes race/ethnicity, gender, LGBT identity, age, disability status, and English fluency, as well as a range of descriptive information designed to provide context for the reason for the stop, what occurred during the stop, and the resolution of the stop. The purpose of collecting this data is to attempt to systematically document and analyze detentions and/or searches of all individuals to determine whether disparities occur depending on race and/or identity. For this year’s Report, the Board presents stop data analyses focused on the race/ethnicity of the person stopped.9 Addressing racial profiling was a driving force in enacting RIPA. The different types of analyses used in this year’s report were included after significant discussion in Board subcommittee meetings, full Board meetings, and input by members of the public. The analyses were conducted to answer the question of whether the perceived race/ethnicity of a stopped individual plays a role in whether they are stopped and/or in the actions an officer takes during a stop. In future reports, the Board intends to focus its analyses on other demographic characteristics of this rich dataset. The decisions made, or actions taken, by the officer can be broken into two types: “pre-stop” and “post-stop.” “Pre-stop” decisions refer to an officer’s decision to stop an individual in the first place. Our pre-stop inquiry analyzes the number of stops of members of the various perceived racial and ethnic groups. This analysis is important because it gives us the ability to examine whether different groups are stopped at different rates, which might indicate that potential bias is present. Because of the difficulty in establishing “benchmarks” – meaning how people would behave in an unbiased world – we have employed several established methodologies to analyze Wave 1 stop data and consider whether the data indicates evidence of racial bias in officers’ pre-stop decisions. First, we compared the demographics of persons stopped to two datasets intended to approximate the general population of residents and drivers, respectively, within the jurisdictions of the Wave 1 LEAs. Specifically, the two datasets we used are (1) the weighted residential population data from the American Community Survey (ACS) (to obtain a resident population benchmark) and (2) the not-at- fault vehicle collision data from a database maintained by the California Highway Patrol (CHP) (to obtain a driver population benchmark). In addition to these population comparisons, we also analyzed the Wave 1 stop data using the veil of darkness methodology. As discussed in prior Board Reports10, this methodology compares stop frequencies during daylight hours, when it could be more likely for an 8 RIPA requires that the demographic information be recorded based upon the officer’s perception, meaning that an officer should not use information from documents or ask individuals directly about their demographic information when completing the stop data form. However, nothing in RIPA prohibits an officer from obtaining such information within the course and scope of their lawful duties. 9 Although the data collected contains officers’ perception of various identity groups and other demographics, this chapter focuses only on their perceptions of race/ethnicity. See the Technical Report for analyses of the data from more identity groups, as well as disaggregated statistical information for each agency. 10 See page 23 of the 2019 RIPA Board report for an explanation of the Veil of Darkness methodology. 20 officer to perceive race, to stop frequencies at night, when it could be more difficult for an officer to perceive race before stopping someone. Another way to get around the issue of benchmarks is to examine post-stop decisions made by the officer. Conducting a search, for example, is conditional on already having stopped an individual. Thus, we can be more confident in comparing the rates at which different identity groups are searched because we know for certain in calculating these ratios what the denominator is: people who have already been stopped. Searches are worth exploring for another reason – they come with their own outcome, namely whether or not the search resulted in, or yielded, the recovery of any contraband or evidence. The yield rate is a measure of the “efficacy of the search.” If the success of searches (i.e. the search yielding contraband) differs across different identity groups, it could be indicative of officers having higher or lower thresholds for searching some groups relative to others and it allows for a stronger case that bias may be a driving factor for searching an individual, as opposed to some other variable like crime rate. We also examined the enforcement rates by race and ethnicity, meaning the rate by which an individual who was stopped is given a citation and/or arrested as a result of the stop. To introduce these methodologies, we first set forth the data regarding the perceived racial and ethnic identity demographics of individuals stopped by the Wave 1 agencies. We then present the results by race and ethnicity for the other elements of the stop, beginning with the reported conditions underlying an officer’s decision to initiate the stop, such as the primary reason for the stop and the circumstances leading to the stop. We then apply the methods discussed above in an effort to see whether the data demonstrate evidence of potential bias in officer pre-stop and post-stop decisions. Summary of Main Results The Board’s analysis of Wave 1 data suggests that officers from these agencies stopped each racial or ethnic group at frequencies that differed from both the weighted ACS residential population estimates and the CHP driver information. These differences were most pronounced for Black individuals, who composed a significantly larger proportion of the individuals who were stopped than they did in either of the two comparison datasets (i.e., the weighted residential population or the driver population). The opposite was true for Asian individuals; Asian individuals represented a smaller proportion of the individuals officers stopped than they did in the comparison datasets. Using the veil of darkness method, the analysis of Wave 1 “Perceived” Identity data shows that stop frequencies differed between racial or ethnic groups based on the level of presumed visibility All racial and ethnic groups given the time of day. Individuals perceived as Pacific referenced in this section are Islander had the highest proportion of their stops occur in based on the reporting officer’s the light. Officers stopped White individuals almost equally perception of the race or in the light and dark. A higher proportion of stops of Black individuals were in the dark hours as opposed to the light ethnicity of stopped individuals. hours. Officers may perceive individuals differently than how As for post-stop outcomes, using the yield rate analysis, the data showed that certain groups of people of color may the individuals self-identify. experience higher degrees of scrutiny by law enforcement compared to White individuals, particularly with respect to search activity. For example, officers searched Hispanic, Black, Native American, and Multiracial individuals at a higher rate than they 21 searched White individuals, despite discovering contraband on members of these groups less frequently when searched. Finally, Wave 1 data shows that the outcome of an enforcement action varied by racial or ethnic group, with Native American and Black individuals having the highest arrest rates and the lowest rates of citation. Middle Eastern/South Asian and Asian individuals had the highest citation rates and among the lowest arrest rates. As discussed in prior Board Reports, any one methodology that aims to evaluate bias suffers from some limitations, suggesting that it is often useful to employ multiple methodologies. Therefore, the use of certain methodologies this year should not be interpreted to mean that the Board will limit itself to these methodologies in future Board reports. Indeed, to gain a fuller understanding of the issues underlying the Board’s goals to develop policy recommendations based upon fact-based evidence, the Board welcomes suggestions from all stakeholders – including academics, law enforcement and the community – about supplemental analysis or alternative methods to examine the stop data in the future. Stop Demographics Wave 1 agencies submitted data regarding stops of more than 1.8 million individuals. RIPA requires officers to record a person’s identity based upon the officer’s perception. Officers may not ask individuals to self-identify their identity group when completing the stop data form. Because of this, the data reflects what the officer perceived the individual’s identity group to be. Of the approximately 1.8 million reported stops, individuals perceived by officers as Hispanic (39.8%) constituted the highest proportion of stopped individuals, followed by White (33.2%), Black (15.1 %), Asian (5.5%), Middle Eastern/South Asian (4.4%) and all other groups (2%; includes Pacific Islander, Native American, and Multiracial11 individuals; see Figure 1). Figure 1. Race/Ethnicity Distribution of Stopped Individuals 11 Officers can select multiple perceived identity categories per stopped individual, if appropriate. For example, an officer could perceive a person as being both White and Black. In our analyses, we categorize all such persons as Multiracial. 22 Decision to Stop Reason for stop: Across all racial and ethnic groups, the most common primary reason officers reported for initiating a stop was a traffic violation, which includes moving and non-moving violations and equipment violations (84.8 percent of all stops; see Figure 2).12 Approximately 85 percent of stops of White and Hispanic individuals were stopped for traffic violations, while 76 percent of stops of Black individuals were for traffic violations. For Asian and Middle Eastern/South Asian individuals, traffic violation was the reason given for initiating 93.6 percent and 94.9 percent of the stops, respectively. The second most common reported reason for stop was reasonable suspicion of criminal activity (11.4 percent of all stops), referred to as “reasonable suspicion” hereafter (see Figure 2).13 Black individuals were stopped for reasonable suspicion in 19.5 percent of their stops, while 10.8 percent of stops of White individuals and 10.6 percent of stops of Hispanic individuals were for reasonable suspicion. Only 3.6 percent of Middle Eastern/South Asian individuals were stopped for reasonable suspicion. All other reasons for stop constituted less than 4 percent of the data. 14 Figure 2. Primary Reason for Stop by Race/Ethnicity 12 See Technical Report Section 1 Table 2.3.2 for the racial/ethnic breakdown by traffic violation subtype. 13 The Board understands that an officer may initiate contact with a person as part of his/her community caretaking function without suspecting that the person is engaged in criminal activity. However, officers currently must record community caretaking stops under the “reasonable suspicion” reason for stop. Officers indicated that 3.5 percent of stops initiated due to reasonable suspicion were for community caretaking purposes. This constituted only 0.4 percent of stops overall. Since a percentage this small would not be viewable in Figure 2, community caretaking stops were not separated out from the reasonable suspicion stops. 14 Other reasons for stop included mandatory supervision (0.6 %), warrants (0.7 %), truancy (0.3 %), possible violations of the Education Code (<0.1 %), to determine whether student violated school policy (>0.1 %), or consensual encounters that resulted in a search (2.2 %). We aggregated these reasons for stop into the category labeled “Other” in Figure 2. 23 Stop circumstance: Stops take place within a broader context. Stops can be initiated either by an officer (“officer-initiated stop”) or in response to a call for service, radio call, or dispatch (“call for service”).15 A call for service is not a reason for a stop. Whether or not a person was stopped in response to a call for service provides additional information that is helpful to contextualize stop data. Key Terms: Stop Circumstance Approximately 5 percent of all stopped individuals Call for service: when an officer were reportedly stopped in response to a call for indicates that the stop of an individual service, as opposed to a stop initiated by an officer was made in response to a call for (see Table 4). This percentage varied by race/ethnicity, but no more than 8 percent of service, radio call, or dispatch. stopped individuals from any racial or ethnic group Officer-initiated stop: when an officer were stopped in response to calls for service. does not indicate that the stop of an The Wave 1 data also shows that individuals of individual was made in response to a different racial or ethnic groups varied in their stop call for service, radio call, or dispatch. rates for officer-initiated stops and calls for service (see Figure 3).16 Table 4. Stop Circumstance by Race/Ethnicity Race/Ethnicity of Stopped Individual Stop Middle Eastern/ Pacific Native Circumstance White Hispanic Black Asian Multiracial South Islander American Asian Officer 568,900 686,017 251,291 96,734 78,171 10,047 3,665 19,851 Initiated 95.2 % 95.8 % 92.7 % 97.3 % 97.8 % 94.9 % 94.3 % 93.5 % Call for 28,865 30,012 19,897 2,713 1,746 537 220 1,388 Service 4.8 % 4.2 % 7.3 % 2.7 % 2.2 % 5.1 % 5.7 % 6.5 % 597,765 716,029 271,188 99,447 79,917 10,584 3,885 21,239 Total 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 15 Officers are required to indicate if a stop was in response to a call for service (also known as a radio call or dispatch). An interaction that occurs when an officer responds to a call for service is only reportable if the interaction meets the definition of “stop” for data collection purposes, meaning any detention by a peace officer of a person or any peace officer interaction with a person in which the officer conducts a search. 11 CCR § 999.224. This information is collected independently from the reason for a stop. 16 “Officer-initiated stops” are defined as any stop where an officer did not indicate that the stop of an individual was made in response to a call for service, radio call, or dispatch. 24 Figure 3. Stop Circumstance by Race/Ethnicity Comparisons to Reference Data As noted above, several methodologies can assist researchers in analyzing stop data to determine the existence of racial bias. As will be discussed below, there are notable concerns with relying entirely on one comparison method. Accordingly, our analysis instead presents the results of three separate methods designed to provide reference points from which to compare the stop frequencies by racial/ethnic group in these data. These methods contextualize stop frequencies using: (1) residential population data; (2) vehicle collision data; and (3) light condition data. Residential population data: We used residential population estimate data from the 2017 American Community Survey (ACS) to provide a contextual residential benchmark for the race/ethnicity of individuals stopped by Wave 1 agencies during the data collection period.17 The United States Census Bureau administers the ACS annually. Our weighting methodology made the ACS data more reflective of the areas within the jurisdictions of Wave 1 agencies, rather than the state or country as a whole.18 Figure 4 displays the racial/ethnic distribution of: (1) stopped individuals from the 2018 data; and (2) estimated residential population of the areas within the jurisdiction of Wave 1 agencies.19 Because the CHP conducted more than half of the stops during the data collection period, we also provide the residential population data table excluding CHP data in the Technical Report.20 17 At the time we sourced the ACS data (October 2019), 2017 was the most recent year available. 18 For a description of the weighting scheme, see the ACS table notes in the Technical Report Section 1 Subsection 2. 19 See Table 2.13.2 in the Technical Report for a weighted ACS breakdown by race for all agencies without California Highway Patrol data. 20 See Table 2.13.2 in the Technical Report for a weighted ACS breakdown by race for all agencies without CHP data. In general, when exempting CHP from analysis, the disparities between stop frequencies and residential population representation increase for Asian, Black, Hispanic, and White individuals. Of these racial/ethnic groups, Black individuals represented a larger proportion of stopped individuals than their share of the residential population data. The opposite was true for Asian, Hispanic, and White individuals. 25 Figure 4. Residential Population Comparison to Stop Data Considerations for and limitations of residential population data: Like all approaches for examining law enforcement stop data, there are important considerations and limitations to recognize when using residential population data within this context. To start, RIPA stop data regulations and the ACS categorize racial/ethnic groups differently (e.g., RIPA regulations explicitly include Israeli individuals in the Middle Eastern/South Asian group, but the ACS does not have an Israeli ethnic category). ACS data also have a category for “Other,” which we could not map to any RIPA race/ethnicity group. Additionally, race/ethnicity information collected for RIPA is based on officer perception, while ACS respondents self-identify their own race/ethnicity. This distinction reflects a difference in purpose between the two databases. The objective of the stop data is to approach the problem of racial and identity profiling, which is why the agencies collect the officer’s perception of race/ethnicity. The ACS, on the other hand, is to provide an accurate representation of information regarding community residents (i.e. social, economic, housing, and demographic characteristics). The RIPA and ACS data collection also occurred during different years (the second half of 2018, and 2017, respectively). The ACS data comparison has other limitations. ACS contains information collected from residents within particular areas. However, officers often stop individuals who are not residents of the areas where the stops take place, but rather are in those areas for other reasons (e.g., going to work, going shopping, visiting friends/family, etc.). Jurisdictions likely vary in the proportion of non-residents they stop, but the stop data does not contain information regarding a person’s residence.21 Moreover, 21 Missouri is an example of a state that is collecting this information, to an extent. The Missouri Attorney General’s Office added data collection procedures to collect information on the residency of stopped individuals for vehicle stops in 2018. This information is available in Appendix C of the 2018 Vehicle Stops Report, available 26 some locations tend to have large-scale events (e.g., concerts, parades, conferences, etc.), are tourist destinations, or have large populations of individuals experiencing homelessness, all of which may present considerations that are even more difficult to account for. Furthermore, officers may concentrate their patrol efforts in certain areas and thus may not have equal probabilities of encountering residents of all areas in their jurisdiction. Additionally, ACS data may not accurately count certain groups that may be less inclined to respond to surveys (e.g. homeless or undocumented individuals). For all of these reasons, the demographics (perceived or actual) of the population of people stopped by law enforcement may not always match the self-reported demographics of residential populations at the city, county, or state level.22 Vehicle collision data: Another type of data that some studies have employed to provide context to stop data is vehicle collision data. Accordingly, as an alternative set of comparison data to ACS, we also provide vehicle collision data as context for the RIPA stop data. California law enforcement agencies submit data gathered from collision scenes to the CHP. The CHP stores these data in a database called the Statewide Integrated Traffic Records System (SWITRS).23 We obtained a dataset containing all reported collision records from reporting agencies for calendar year 2018. We limited the data from SWITRS to not-at-fault parties from collisions reported by Wave 1 agencies, with the idea that this group of drivers is selected somewhat randomly because another driver struck them with their vehicle.24 This is important because the purpose of the data we selected is to serve as a benchmark of drivers in general, not just the less-skilled or inattentive drivers that may tend to be at fault more frequently. We then employed a similar method used for the ACS data to make the SWITRS data more reflective of stop activity that occurred in the jurisdictions of Wave 1 agencies. Figure 5 displays the distribution of the perceived race/ethnicity of (1) individuals stopped for traffic violations from the 2018 RIPA data and (2) the weighted not-at-fault party SWITRS data reported by Wave 1 agencies in 2018. This figure is specific to traffic violations, which constitute a majority (84.8%) of stops in the RIPA stop data (see Figure 2). As we did with the residential population data, we also provide these data with CHP excluded in the Technical Report.25 at https://ago.mo.gov/docs/default-source/public-safety/2018appendixc.pdf?sfvrsn=2. The experiences of Missouri law enforcement agencies may not directly compare to those of California law enforcement agencies, however. 22 For more information on this issue, see previous RIPA reports or the following publication by the United States Community Oriented Policing Services, available at https://ric-zai-inc.com/ric.php?page=detail&id=COPS-P044. 23 See https://www.chp.ca.gov/programs-services/services-information/switrs-internet-statewide-integrated- traffic-records-system for more information on SWITRS. 24 Not all studies that employ vehicle collision data utilize only the not-at-fault party data (e.g., Withrow, Brian L., and Howard Williams. “Proposing a Benchmark Based on Vehicle Collision Data in Racial Profiling Research.” Criminal Justice Review 40, no. 4 (2015): 449–69. https://doi.org/10.1177/0734016815591819.) 25 See Table 2.13.4 in the Technical Report for a weighted SWITRS breakdown for race/ethnicity without CHP data. In general, when CHP data is excluded from analysis, the disparity between the stop data and the vehicle collision data increased for Black and White individuals, as well as the group categorized as “Other” for this analysis (Middle Eastern/South Asian, Multiracial, Native American, and Pacific Islander individuals). Of the three groups where disparities increased by exempting CHP, Black individuals comprised a greater proportion of those stopped relative to their representation in the collision data. The opposite was true of White and “Other” individuals. 27 Figure 5. Vehicle Collision Data Comparison to Stop Data Considerations for and limitations of vehicle collision data: As with residential population data, there are important caveats about making SWITRS Quick-Reference Limitations comparisons between RIPA and SWITRS data. 1. RIPA stop data collection and SWITRS categorize racial/ethnic First, SWITRS collects groups differently. race/ethnicity 2. RIPA data does not expressly identify drivers; rather, it information for fewer identifies persons stopped for traffic violations. groups than are 3. Officers may be incorrect in determining which party was at present in the RIPA fault, in some cases. regulations. As a 4. Identity groups could differ in their likelihood of being captured result, some RIPA race/ethnic groups in the SWITRS data. were aggregated into 5. SWITRS data collection policies are not uniform across the an “Other” category entire state. for Figure 5.26 Second, officers may collect race/ethnicity information differently between the two datasets; RIPA relies solely on officer-perception data, while officers may enter the race/ethnicity data in SWITRS after examining documentation or having an individual self-identify. Third, there is no specific data element to differentiate motorists from pedestrians in the RIPA dataset; the closest within the RIPA data is to examine stops that officers indicated they initiated for traffic violations. However, several Vehicle Codes regulate pedestrian behavior; this means that some individuals stopped for traffic (e.g. Vehicle Code) violations could be pedestrians. Fourth, although there is a variable that indicates what party was at fault in the SWITRS database, it is possible that officers are incorrect in determining which party 26 In this analysis, the “Other” category consists of Middle Eastern/South Asian, Multiracial, Native American, and Pacific Islander individuals. 28 was at fault when entering the data in some cases. Fifth, the likelihood of becoming a not-at-fault party to a vehicle collision could differ amongst identity groups in some areas. Sixth, not all agencies in the state respond to collisions where there were no injuries and not all agencies determine which party was at fault for the collision, so not all collisions are reflected in the dataset.27 Lastly, fewer empirical studies employ this type of data than residential population data; in part, this is because it is generally harder to access than residential population data made readily available by the U.S. Census Bureau, meaning that there is less known regarding other potential issues about this benchmark. Light condition data: The proportion of stops represented by different racial or ethnic groups varied by time of day (see Figure 6).28 White individuals composed a higher percentage of stops during daylight hours, as compared to evening hours when there was less light out. Conversely, Black and Hispanic individuals composed a higher relative percentage of stops during evening hours than daylight hours.29 Hourly stop shares for Asian persons were relatively consistent over time. These data could indicate that light conditions may affect the likelihood of being stopped differently by race/ethnicity. Figure 6. Stop Distribution by Race/Ethnicity by Hour of the Day To more directly test whether light conditions affect stop frequencies, the Board adopted a method introduced by two researchers working for the RAND Corporation on a study of Oakland Police 27 All Wave 1 agencies reported some parties in their 2018 SWITRS data to be at-fault. This limitation of SWITRS data may be more relevant in future years when more agencies are included in the analyses. 28 Middle Eastern/South Asian, Multiracial, Native American, and Pacific Islander individuals are grouped into the “Other” category in this figure. 29 Hispanic and White individuals were stopped in the highest proportions at all hours of the day. 29 Department vehicle stop data.30 These researchers suggested that differences in stop frequencies by race/ethnicity could be contextualized using civil twilight data.31 This approach, often referred to as the “veil of darkness” (VOD), hypothesizes that if officers target some individuals for stops more than others based on their race, evidence of profiling should be most apparent during daylight when the race of drivers is presumably most visible. Conversely, if race were more difficult to see in darkness, then officers would be less able to rely on race as a factor in making decisions about whom they stop during the night. Since the original study that established the VOD approach, many other studies have adopted variations of this framework to analyze stop data. RIPA Board’s decision to include VOD methodology: The inclusion of the VOD test was a topic of robust discussion at the November 20, 2019 Board meeting. Some members of the RIPA Board expressed concerns about the VOD methodology while other members believed it was beneficial to include this analysis. Some Board Members presented the following arguments for the exclusion of the VOD analysis: • VOD is based only on traffic stops during a certain period in the day. • The CHP stop data makes up more than half of the stops analyzed in the VOD test and the nature of their stops are categorically different than those of other agencies. First, the number of traffic violation stops varied widely across Wave 1 agencies: for example, they made up 98.5 percent of the CHP’s stops, but only 42.5 percent for San Diego Police Department’s stops. Second, the CHP noted that it was more difficult to perceive the identity of people stopped on the highway with or without daylight. In response, some Board members believed the test was an unfavorable method for use on data collected for stops on highways. • The Board believed that this methodology did not adequately address other limitations such as lighting from street lights in urban areas; this was of additional concern given that the agencies that submitted data in 2018 were primarily ones that police urban areas. • Several published studies have shown that with the loss of light during daylight savings time there is an increase in crime; this might alter the behavior of law enforcement officers and it may interact with race in a complex way. • Compared to other methods utilized in this report, the Board believed that the VOD is excessively technical and, therefore, requires a disproportionate amount of explanation to communicate how the analysis was performed. The report gives the residential data one page of analysis, the collision data one page of analysis, and the VOD five pages of analysis. 30 Grogger & Ridgeway, Testing for Racial Profiling in Traffic Stops from Behind a Veil of Darkness (2006) RAND Corporation. 31 Civil twilight is defined as the illumination level sufficient for most ordinary outdoor activities to be done without artificial lighting before sunrise or after sunset. Therefore, it is dark outside when civil twilight ends; civil twilight ends when the sun is six degrees below the horizon. 30 • Given the complicated framework underlying the VOD analysis, the subtleties of results produced by these methods are difficult to interpret and may lead to confusion. The Board was concerned that it may seem that it was providing conflicting results to the public. Other Board members made the following arguments for inclusion of the VOD analysis: • In the 2019 Report, the Board identified VOD as one of several methodologies that might be used in analyzing the data and excluding the methodology now that the analysis had been completed might signal a lack of transparency to some stakeholders. • This methodology has a research base, including articles published in academic publications, such as the Journal of the American Statistical Association. • There is a desire to present the results from multiple analytical methods. This will allow for judgments to be made about the appropriateness of each methodology for agencies to analyze their data. • There is an interest in seeing if it will be possible to draw comparisons between the VOD analyses in this year’s report to those in the future when a larger dataset will be available. After the discussion, a motion was made to exclude the VOD analysis pending further review by the Stop Data Subcommittee, given the concerns with whether the VOD test had validity. The Board vote was evenly divided (five ayes, five nays, one abstention) and thus the motion to remove the VOD test did not pass. The Board is including the VOD analysis in this year’s report with the hope that it will receive feedback from the community, academics, and law enforcement with respect to the efficacy of using this type of analysis in the future. Certainly, the Board has a strong interest in continuing to pursue multiple different analytical methods that will be useful to both the public and law enforcement moving forward. Accordingly, the Board requested that the Stop Data Subcommittee continue to review VOD and any other methods of which it becomes aware and to make recommendations to the full Board with respect to methodologies to include in future reports. Although the VOD methodology has its own limitations, it avoids issues that surround population- based benchmarking. Instead, it compares the proportion of stopped individuals of a given race during daylight to the group’s proportion during dark hours. Thus, we employ the VOD approach as one of the multiple comparative approaches in this report to analyze the stop data. Veil of Darkness methodology: The VOD technique examines stops that occur during a standardized inter-twilight period, or the time of day that is dark during Standard Time but light during Daylight Savings Time. By limiting the analysis to only those stops that occurred during this period, frequency comparisons are less susceptible to factors that vary by time of day (e.g... commuting patterns). To identify the inter-twilight period for the 2018 data, we sourced civil twilight times for each stop date and location using the United States Naval Observatory database.32 We bounded the inter-twilight period using the earliest and latest instances of civil twilight for each location across the entire reporting period (approximately 4:54 pm to 9:30 pm). As shown in Figure 7, stops that occurred between the earliest end of civil twilight and the latest end of civil twilight would be included in the analyses. The blue line represents the end of civil twilight for a given day. Stops that occurred with 32 This information is sensitive to location. Civil twilight can vary by over an hour on the same day across the state. 31 sunlight fall under the blue line, while those without sunlight occurred above the blue line. The large dip in the trajectory of the blue line on November 4th is when the time switched from Daylight Savings Time back to Standard Time. Figure 7: Inter-Twilight Period Example Using 2018 Data for San Francisco, CA Only officer-initiated stops for traffic violations were included in this analysis for several reasons. First, many studies that employ a VOD framework utilize vehicle stop data only; traffic violations are the closest proxy to vehicle stops found in RIPA stop data. Second, the assumptions underlying VOD are most likely to hold true for stops made outdoors, for people who are obscured by their vehicle, and for stops where officers are not called to the scene; these criteria are truer of stops made for traffic violations than those made for other reasons, including reasonable suspicion. It is important to note that stops made for reasonable suspicion may often be more discretionary than those made for traffic violations, and may therefore be more likely to reveal instances of racial profiling; however, these stops are more likely to introduce additional confounding factors that violate the assumptions of VOD. Accordingly, reasonable suspicion stops are included in the analyses provided in other sections of this report. 32 Considerations and limitations of VOD Quick-Reference Limitations the VOD: The VOD approach was developed to address limitations of 1. Reduced visibility under darker conditions does not benchmarking comparisons; mean no visibility, so officers may still be able to however, this does not mean that perceive race prior to initiating stops. the VOD is without limitations of its 2. The likelihood of some identity groups to commit own. To start, even under dark certain offenses or be stopped for certain offenses outdoor conditions with no artificial light, it is likely that some could differ across lighting conditions. officers are able to perceive the 3. Seasonal differences in driving patterns of certain race of individuals from close identity groups could also influence the identity group distances. Additionally, many composition of drivers. patrol areas have some artificial 4. The method only examines data from a set period of light (e.g. streetlights, store time and for a single type of stop (traffic violations). signage, porch lights, etc.) that reduces the degree to which 5. Officers could use observable proxies to guess the race darkness may hinder their ability to of drivers. perceive race. There may also be certain types of violations (e.g. equipment violations) that some racial groups may have different propensities to commit due to economic or other reasons, which can be differently visible depending on whether it is light or dark outside.33 Drivers belonging to some identity groups may also change their driving behavior based on the perceived likelihood of officers being able to correctly perceive their identity group membership.34 Separate from the issue of lighting conditions is the potential issue that seasonal differences in driving patterns of certain groups could also influence the racial composition of drivers on roadways. The VOD test also only examines data from within the inter- twilight period, meaning that obtaining large sample sizes for smaller racial groups (e.g. Native American persons) requires many reporting agencies or a dataset that contains more historical data than the RIPA dataset does currently. The VOD is also a test best fit for vehicle stop data, but RIPA data do not explicitly differentiate vehicle stops from pedestrian stops; therefore, analysts must narrow the data using an approximate method by examining traffic violations. Lastly, there may be observable proxies for race (e.g., the make and model of the vehicle, the location of the stop, etc.) that officers could utilize to guess the race of drivers that could affect the assumptions of the test. Stop frequencies by race and sunlight availability: Across the reporting period, there was a near 50/50 split between the proportion of individuals stopped during the inter-twilight period under light (50.1%) and dark conditions (49.9%). White persons had the closest stop distribution to a 50/50 split. Asian, Middle Eastern/South Asian, and Black individuals had slightly more of their members stopped under dark conditions than light within the inter-twilight period (50.3% - 51.2%). Pacific Islander individuals 33 Ritter, Joseph A. “How Do Police Use Race in Traffic Stops and Searches? Tests Based on Observability of Race.” Journal of Economic Behavior & Organization 135 (2017): 82–98. https://doi.org/10.1016/j.jebo.2017.02.005. 34 Kalinowski, Jesse, Ross, Stephen L. & Ross, Matthew B. “Endogenous Driving Behavior in Veil of Darkness Tests for Racial Profiling.” Working Paper, Human Capital and Economic Opportunity Global Working Group, The University of Chicago, February 2017. 33 had the highest proportion of their members stopped in the light (57.0%), followed by Native American, Multiracial, and Hispanic individuals. Under the assumptions of VOD, having a higher proportion of a group stopped under light conditions may be considered as evidence of bias towards that group. Figure 8 displays the proportion of each race/ethnicity group stopped under each condition. Compared to White individuals, Multiracial, and Pacific Islander individuals were more likely to be stopped in the light, while Black individuals were more likely to be stopped in the dark.35 Given that CHP made over half the stops during the data collection period, and that most of the stops that CHP made were for traffic violations, we also conducted this analysis without CHP data and provide the table in the Technical Report.36 Figure 8: Inter-Twilight Stop Frequencies by Race/Ethnicity 100% 90% 80% 70% 49.7% 48.8% 50.5% 49.5% 53.5% 54.5% 57.0% 50.0% 60% 50% 40% Light 30% 20% 50.3% 51.2% 49.5% 50.5% 46.5% 45.5% 43.0% 50.0% Dark 10% 0% Asian Black Hispanic Middle Multiracial Native Pacific White (9,428) (25,045) (66,682) Eastern/ (2,170) American Islander (54,546) South Asian (389) (931) (8,333) Post-Stop Outcomes Search rates: Conducting a search of a person or their property was the most common reportable action officers took during a stop. Overall, officers conducted a search of a person or their property in 9.9 percent (n = 178,975) of the stops reported.37 Figure 9 shows the percentage by race/ethnicity of all individuals who were subjected to a search of their person and/or property.38 The racial/ethnic 35 We used logistic regression and the same model specification as Grogger & Ridgeway, 2006. For detailed information regarding the model specifications and results, see Table 2.14.3 of Section 1, Subsection 2 in the Technical Report. Tables 2.14.5 through 2.14.6 also display alternative VOD analyses without California Highway Patrol and for the change in stop frequency before and after daylight savings. 36 See Table 2.14.4 in the Technical Report for VOD regression results excluding California Highway Patrol data. Compared to analyzing all agencies together, excluding CHP in subsequent analyses produced contrasting results. With the exception of Hispanic persons, the strength of the disparity reversed for all other groups. Specifically, if the disparity in stop probability at night was significant for a group in the full analysis, significance was lost with the exclusion of CHP. But, if the disparity in stop probability was not significant in the full analysis, significance was gained with the exclusion of CHP. For example, the disparity between Black and White individuals was significant when all data was included, but was no longer significant when CHP data was excluded. 37 This includes both searches of the person (9.2 percent of individuals) and searches of their property (4 percent of individuals). Officers could conduct both a person and property search of the same person, which is why both these search types taken together amount to 9.9 percent of individuals, rather than 13.2 percent. These figures do not include canine searches (0.1 % of individuals). 38 Middle Eastern/South Asian (2.8 %) and Asian (3.1 %) persons had lower search rates than White persons. 34 group with the highest percentage of stops where a search occurred was Black individuals; stops of Black individuals involved a search 18.7 percent of the time, while the racial/ethnic group with the next closest search rate (Multiracial individuals) had a search rate less than two thirds as high as Black individuals. Officers searched Black individuals whom they stopped at a rate that was 2.9 times the rate they searched White individuals. Figure 9. Search Frequency by Race/Ethnicity Basis for search: We created search discretion categories in our data, adapting what previous studies have done to explore the issue of officer discretion for searches.39 We examined searches in two categories: “higher discretion” and “lower discretion” (Figure 10).40 Administrative, or “lower discretion,” searches are most often required under department policy and include those performed following an arrest, pursuant to a warrant, or after impounding a vehicle.41 On the contrary, “higher discretion” searches are those where officers have the most flexibility in determining who to search, and include only those occurrences where consent is the only basis provided.42 Individuals for whom 39 See Chanin, J., Welsh, M., & Nurge, D. (2018). Criminal Justice Policy Review, 29(6–7), 561–583 or Mosher, C., & Pickerill, J. (2011). Seattle University Law Review, 35(3), 769. 40 For a more thorough review on the distinctions between lower and higher discretion searches, see Chanin et al. (2018). For the purposes of this report, searches conducted with a warrant were also included in the “low” discretion category. 41 Corresponding bases for search found in the RIPA Stop Data include incident to arrest, search warrant, and vehicle inventory. 42 Also of note, some studies include “Terry” searches or frisks (see Terry v. Ohio) in the higher discretion search category as well. Terry Searches include those justified as a protective search (pat search) for weapons based on reasonable belief that the person is dangerous or carrying a weapon. Terry searches do not have a direct analog in the RIPA regulations. However, the Board has received public comments about proxies for Terry searches in the stop data. In response, an additional version of the yield rate analysis using an alternate higher-discretion categorization was included in the Technical Report (Table 2.15.8); the alternate higher-discretion scheme includes searches based on consent, officer safety, or suspected weapons and excludes all other potential search bases. See footnote 45 for a synopsis of how this alternative categorization scheme affected results. 35 officers provided other search bases (e.g. canine detection, officer safety) are not included in either of the two discretion categories. Thus, these individuals were not included in the discretion level analyses. Figure 10 displays the racial and ethnic distribution of individuals searched by officers in higher and lower discretion searches. Figure 10. Search Discretion by Race/Ethnicity Search efficacy: There are a number of factors that Key Terms an officer may use when deciding to undertake a discretionary search. A central factor is the strength Yield rate: proportion of searched of an officer’s suspicion that the stopped individual individuals found in possession of has contraband and that a search will reveal that contraband or evidence. contraband. If an officer’s suspicion is a primary Officer-discretion level: level of factor and the officer is not using race as part of discretion available to the officer in their decision to search, then we would expect deciding to conduct a search. individuals would have to exhibit roughly the same • Higher: includes searches where the level of suspicious behavior (e.g. the frequency of only listed basis for search was furtive movements) for an officer to decide to “consent given”. conduct a search. We also would expect that the • Lower: incident to arrest, vehicle more suspicious a person appears, the more likely it is that they have contraband. Combining these two inventory, and search warrants. assumptions creates a statistical test for whether or not officers apply different standards to people from different identity groups. If officers are less likely to find contraband after searching people of a particular identity group, then we assume this means that the searched individuals in that identity group are objectively less suspicious, and thus subject to search because of their identity rather than any suspicious behavior. Alternatively, if searches yield comparable rates of contraband and evidence across all racial groups, this would suggest officers’ thresholds of suspicion justifying a search are similar across race. The following sections employ various analyses to explore this possibility. 36 We examine search yield rates in the following sections. A search yield rate is the proportion of individuals that were subject to a search that officers found to be in possession of contraband or evidence.43 Yield rates are calculated in the following manner: !"#$%& () *%+&,ℎ%. /0.121."+34 516ℎ 7(06&+$+0. (& 821.%0,% ∗100 9(6+3 !"#$%& *%+&,ℎ%. /0.121."+34 Search yield rate is a measure of search efficacy. Thus, higher rates indicate that searches were successful and resulted in finding contraband or evidence (a “hit”) more often. Understanding the efficacy of searches can help reveal whether certain identity groups are under a greater degree of unwarranted scrutiny during stops. Before discussing yield rates, it is important to note that conducting searches is not the only way officers discover contraband or evidence. RIPA data collection allows officers to report that they discovered contraband or evidence regardless of whether or not they searched an individual. Wave 1 officers discovered contraband or evidence on 3.4 percent (60,792) of individuals they stopped. Of the individuals who had contraband or evidence discovered during their stop, 65.3 percent (39,676) of individuals were searched, while the remaining 34.7 percent (21,115) were not searched.44 Only searched individuals are included in yield rate analyses. Search yield rates: Figure 11 displays the search yield rates of the racial/ethnic groups collected under RIPA. The search yield rate for White individuals was 24.3 percent. Yield rates were lower for all racial groups of color compared to White individuals (1.8 to 5.6 percentage points lower). This shows that officers were less successful at finding contraband or evidence of wrongdoing when searching individuals of color than White individuals. 43 RIPA regulations do not differentiate between cases where contraband is found in plain view prior to conducting a search versus cases where no contraband or evidence is viewed prior to the search. 44 While 72.7 percent of yields from searches came from drug-related contraband, the most frequently discovered contraband or evidence type from stops without a search was alcohol (43.1%). Black individuals (2.17%) had the highest intra-group rates of contraband discovered in the absence of a search while Middle Eastern/South Asian individuals (0.33%) had the lowest. In this section, we did not perform further analyses surrounding contraband or evidence discovered in cases where individuals were not searched. Future analyses may examine these circumstances. 37 Figure 11. Search Yield Rates by Race/Ethnicity Yield rates by discretion level: In addition to examining overall search yield rates, we examine yield rates based on the level of discretion the officer had in deciding to conduct the search (see Figure 12).45 When officers conducted highly discretionary searches of individuals (only basis was consent), officers had higher yield rates for White persons than for all other racial/ethnic groups. Most racial or ethnic groups also had lower yield rates than White persons for searches where officers are presumed to have less discretion (lower-discretion searches); however, yield rates for Black persons were 1.3 percentage points higher for lower-discretion searches—despite experiencing a smaller proportion of searches with this level of discretion (see Figure 10).46 45 Searches that were not categorized as lower or higher discretion constituted 48.3 percent of stops with searches. See Table 2.15.7 in Section 1, Subsection 2 of the Technical Report for a breakdown of search yield rates by each individual basis for search. 46 Under the alternative higher discretion categorization scheme (see footnote 41), individuals of color, except persons perceived to be Pacific Islander, had lower yield rates than White persons. With the exception of Middle Eastern/South Asian and Native American individuals, yield rate differences between White individuals and other racial or ethnic groups decreased when including searches for officer safety and suspected weapons in the higher discretion category. 38 Figure 12. Search Yield Rates by Search Discretion by Race/Ethnicity Stop circumstance: The stops for 95.3 percent of all individuals were officer-initiated, while 4.7 percent of all stops were in response to a call for service.47 Thus, the findings in the yield rate analysis overall are largely driven by officer-initiated stops. All individuals of color had lower yield rates compared to White individuals overall (see Figure 11). When analyzed calls for service separately to better understand the issue, the difference in yield rates between White individuals and many persons of color was less pronounced.48 It is worth noting that stops made in response to a call for service may or may not be of the subject of the call. Considerations and limitations of search yield rates: Search yield rate tests avoid some of the issues of other tests because yield rates do not require the stop data to be matched with, or compared to, another set of data. However, one consideration when examining yield rates is that there can be observable factors that influence officers’ decisions to search individuals related to the identity of the stopped individual that RIPA stop data collection may not capture. If this were the case, then we could incorrectly attribute this identity-neutral reason for differences in search frequency to identity. 47 CHP conducted the fewest stops in response to a call for service. To ensure the results of the overall yield rate analysis were not driven solely by CHP, we also analyzed the data without their records (Appendix D, Table 7). When we exclude CHP data, the direction of all significant disparities between White and Non-White groups matched the results of analyses from all reporting agencies together (e.g. Asian persons had lower overall rates than White persons regardless of whether CHP data were included). For this reason, the CHP data was included in all results discussed in the main report body. 48 The percentage point difference in yield rates between Multiracial, Pacific Islander, Native American, Hispanic, and Black individuals and White individuals was less when examining only individuals stopped in response to calls for services than when we examined all searched individuals, regardless of the stop circumstance. 39 Further, since the analysis is based on all discoveries of contraband, differences in the frequency with which people in one identity group are very suspicious and would always be searched, can mask racial differences in the frequency with which people who are only slightly suspicious are searched.49 Enforcement Rates for Stops with Searches: To understand how frequently officers searched individuals and then decided to take an enforcement action afterwards, we examined enforcement rates for searched individuals. For the purpose of this report, we define enforcement rates as the proportion of a group of stopped individuals who were arrested or received a citation. We excluded stops where officers listed “incident to arrest” or “vehicle inventory” as a basis for the search.50 After excluding these stops, we learned that officers took enforcement action with 26 percent of the individuals they searched. The proportion of the searched individuals that were subject to an enforcement action varied by race/ethnicity, with Black individuals having the lowest rate (21.2%) and White individuals having the highest rate (33%). Officer-initiated stops with searches appear to drive the overall enforcement rates of searched individuals. When examining only officer-initiated stops with searches, White individuals (35.8%) had higher enforcement rates than all other racial or ethnic groups; Black individuals had the lowest enforcement rates (20.9%). The distribution of enforcement rates for the small proportion of searched individuals who were stopped in response to a call for service was different from the overall and officer-initiated enforcement rates. Enforcement Rates for all Stops: Officers took enforcement action on 60.3 percent of all individuals stopped during the reporting period, ranging from 51.6 percent of Black individuals to 68.7 percent of Asian individuals (Figure 13).51 These trends were driven by officer-initiated stops where Black individuals (52.2%) continued to have the lowest enforcement rates overall and Asian individuals (69.4%) the highest. White individuals (38.9%) had lower enforcement rates than other racial or ethnic groups (41.4 – 49.5%) when analyzing calls for service independently. 49 See page 26 of the 2019 RIPA Board report for an example that illustrates infra-marginality. 50 By definition, these searches would come after the officer had already decided to take enforcement action and therefore do not follow the progression from search to enforcement that this analysis seeks to examine. 51 Enforcement action is a citation for infraction, in-field cite and release, custodial arrest without a warrant, custodial arrest with a warrant, or any combination of these four results of stop. 40 Figure 13. Citation and Arrest Rates by Race/Ethnicity52 Analyzing enforcement by type of offense revealed a more nuanced pattern. Relative to other groups, a lower percentage of Black and Native American individuals were issued citations (36.8% – 38.0%), while Asian and Middle Eastern/South Asian individuals had higher citation rates (57.6% – 61.4%). Conversely, Black and Native American individuals were arrested at relatively high rates (15.2% – 16.0%) compared to Middle Eastern/South Asian and White individuals (7.0% – 11.3%), who had lower percentages of arrests overall (see Figure 13). Ongoing Training to Ensure the Continued Integrity of Data Collection and Submission To gain insight into the specific needs of law enforcement agencies with respect to the technical aspects of data collection and submission to the Department, the Department’s Client Services Program (CSP) facilitated two Lessons Learned sessions during the fall of 2019. The Department’s business, legal, technical, and research teams participated with law enforcement staff representing the fifteen agencies currently collecting stop data (the Wave 1 and Wave 2 agencies), as well as some from the Wave 3 agencies who are scheduled to begin collecting data on January 1, 2021. The goal of the sessions was to elicit feedback on training, outreach, technology, timelines, annual close-out process, the designation and handling of persons’ personally identifiable information and officers’ unique identifying information, as well as responses to Public Records Act requests, data analysis, and future enhancements. The agencies were able to share their experiences and feedback, trade advice, and discuss gaps in training with the Department. These sessions served as an open forum to share the lessons learned during the initial implementation process of the data collection and identified a need 52 The arrest category in Figure 13 includes custodial arrests (both with and without a warrant), as well as in-field cite and releases. 41 for more scenario-based training. The CSP will incorporate the feedback to improve the implementation process for the next group of agencies. Data Integrity Video In May 2019, the RIPA Board released a five-minute video in which six diverse stakeholders address data integrity for the RIPA stop data. The video outlines the role of law enforcement agencies and the Department in performing data integrity checks, as described by Dr. Sharad Goel, Stanford University Assistant Professor and Founder and Executive Director of the Stanford Computational Policy Lab: “The integrity of the stop data is checked at several phases of the collection and analysis process... If discrepancies are discovered anywhere in the [collection/reporting] pipeline, State officials can work with local jurisdictions to improve the quality of collected data.” Dr. Jack Glaser, Professor at the Goldman School of Public Policy at the University of California, Berkeley, and recognized expert on racial profiling, explained what data integrity means and how it is achieved: “Data integrity, at its core, means that the numbers reflect reality. This happens when officers record all stops fully and forthrightly, and when these records are stored and shared consistently and transparently. In order for people to be able to trust the data, it is crucial that reporting requirements and guidelines be consistent across and within departments.” The Data Integrity video is available on YouTube53 and a link is provided on the RIPA Board webpage. 53 California Department of Justice. (2019, May 2). RIPA - Data Integrity [Video file]. Available at https://www.youtube.com/watch?v=F2evScIOFo0&t=3s. 42 Racial and Identity Profiling Policies and Accountability Both the United States and California Constitutions provide for equal protection under the law and the right to be free from unreasonable searches and seizures conducted by government. California law further guarantees these rights for all people, regardless of the actual or perceived race, color, ethnicity, national origin, age, religion, gender identity or expression, sexual orientation, or mental or physical disability of the individual.54 Police action that is biased is illegal and violates these rights. Biased-based policing, furthermore, alienates the public, fosters distrust of police, and undermines legitimate law enforcement efforts.55 As stated by the California Legislature, racial and identity profiling is “abhorrent and cannot be tolerated.”56 RIPA directs the Board to review and analyze “racial and identity profiling policies and practices across geographic areas in California, working in partnership with state and local law enforcement agencies.”57 In its 2019 report, the Board surveyed all California law enforcement agencies subject to stop data reporting on their current policies and practices relevant to preventing racial and identity profiling and their efforts to enhance law enforcement-community relations and reduce bias in policing. The Board found that while most agencies did have a specific policy or portion of a policy addressing racial and identity profiling, there was little consistency in the substance of the policies across agencies.58 In light of this lack of consistency, this year’s report provides model language that law enforcement can include in their bias-free policing policies. This model language is based on existing evidence-based best practices provided in the Board’s last report. The Board provides this language with the caveat that this model language is only a starting point for protecting the constitutional rights of Californians. Bias-free policing is constantly evolving, and thus policies will need frequent updating to track with the latest police practices. The Board encourages law enforcement agencies to collaborate with community members to develop their bias-free policing policies and to adapt the language of the recommended policies to fit the communities they serve. Recommendations for Model Bias-Free Policing Policies A model bias-free policing policy is a stand-alone policy devoted to bias-free policing. It uses clear language, including definitions of relevant terms, and expresses the agency or department’s responsibility to identify and eliminate racial and identity profiling. In addition to stating the agency or department’s core values and its commitment to bias-free policing, a model policy includes relevant federal and state law. A model policy is based on best practices, well researched, and regularly updated with changes in the law or best practices. A model bias-free policing policy includes cross references to other relevant agency policies on subjects such as civilian complaints, stops, use of force, training, and accountability. It also includes references to relevant training that agency or department 54 Pen. Code, §13519.4. 55 Pen. Code, §13519.4, subd. (d)(1)-(4). 56 Pen. Code, §13519.4, subd. (d)(2). 57 Pen. Code, §13519.4, subds. (j)(3) & (A)-(E). 58 Of the 425 law enforcement agencies in the State that were sent the survey, 114 agencies participated, and thus the responses may not be representative of all agencies in the State. The current report focuses on the bias-free policing policies of the eight Wave 1 agencies that began collecting data on July 1, 2018. 43 personnel receive on subjects such as implicit bias, civilian complaint procedures, human and community relations, etc. A model stand-alone policy is easily accessible to both agency personnel and the public. All personnel, including dispatchers and non-sworn personnel, should receive training on the bias-free policing policy. Specific examples of behavior that violates the bias-free policing should be included in either the training or the policy itself. Below is model policy language and definitions that LEAs can consider including in their bias- free policing policies. The Board notes that these recommendations are the floor, and not the ceiling, of best practice recommendations for bias-free policing policies. A. Model Policy Language for Bias-Free Policing Policy • The [agency] expressly prohibits racial and identity profiling. • The [agency] is committed to providing services and enforcing laws in a professional, nondiscriminatory, fair, and equitable manner that keeps both the community and officers safe and protected. • The [agency] recognizes that explicit and implicit bias can occur at both an individual and an institutional level and is committed to addressing and eradicating both. • The intent of this policy is to increase the [agency’s] effectiveness as a law enforcement agency and to build mutual trust and respect with the [city, county or state’s] diverse groups and communities. • A fundamental right guaranteed by the Constitution of the United States is equal protection under the law guaranteed by the Fourteenth Amendment. Along with this right to equal protection is the fundamental right to be free from unreasonable searches and seizures by government agents as guaranteed by the Fourth Amendment. • The [agency] is charged with protecting these rights. Police action that is biased is unlawful and alienates the public, fosters distrust of police, and undermines legitimate law enforcement efforts. • All employees of [agency] are prohibited from taking actions based on actual or perceived personal characteristics, including but not limited to race, color, ethnicity, national origin, age, religion, gender identity or expression, sexual orientation, or mental or physical disability, except when engaging in the investigation of appropriate suspect-specific activity to identify a particular person or group. • [Agency] personnel must not delay or deny policing services based on an individual’s actual or perceived personally identifying characteristics. 44 B. Model Policy Language for Definitions Related to Bias • Racial or Identity Profiling: the consideration of, or reliance on, to any degree, actual or perceived race, color, ethnicity, national origin, age, religion, gender identity or expression, sexual orientation, or mental or physical disability59 in deciding which persons to subject to a stop or in deciding upon the scope or substance of law enforcement activities following a stop, except that an officer may consider or rely on characteristics listed in a specific suspect description. Such activities include, but are not limited to, traffic or pedestrian stops, or actions taken during a stop, such as asking questions, frisks, consensual and nonconsensual searches of a person or any property, seizing any property, removing vehicle occupants during a traffic stop, issuing a citation, and making an arrest.60 • Bias-Based Policing: conduct by peace officers motivated, implicitly or explicitly, by the officer’s beliefs about someone based on the person’s actual or perceived personal characteristics, i.e., race, color, ethnicity, national origin, age, religion, gender identity or expression, sexual orientation, or mental or physical disability. • Implicit Bias: the attitudes or stereotypes that affect a person’s understanding, actions, and decisions in an unconscious manner. These biases, which encompass both favorable and unfavorable assessments, are activated involuntarily and without an individual’s awareness or intentional control. Implicit biases are different from known biases that individuals may choose to conceal. • Bias by Proxy: when an individual calls/contacts the police and makes false or ill-informed claims of misconduct about persons they dislike or are biased against based on explicit racial and identity profiling or implicit bias.61 When the police act on a request for service based in unlawful bias, they risk perpetuating the caller’s bias. Members should use their critical decision-making skills, drawing upon their training to assess whether there is criminal conduct. • Reasonable Suspicion to Detain: reasonable suspicion is a set of specific facts that would lead a reasonable person to believe that a crime is occurring, had occurred in the past, or is about to occur. Reasonable suspicion to detain is also established whenever there is any violation of law. Reasonable suspicion cannot be based solely on a hunch or instinct. • Detention: a seizure of a person by an officer that results from physical restraint, unequivocal verbal commands, or words or conduct by an officer that would result in a reasonable person believing that he or she is not free to leave or otherwise disregard the officer.62 • Reasonable Suspicion to Conduct a Pat Search: officers are justified in conducting a pat search if officers have a factual basis to suspect that a person is carrying a weapon, dangerous instrument, or an object that can be used as a weapon, or if the person poses a danger to the safety of the officer or others. Officers must be able to articulate specific facts that support an 59 Some agencies include other personal characteristics in their racial or identity profiling policies, such as socioeconomic status or immigration status. 60 Cal. Pen. Code, § 13519.4, subd. (e). 61 Fridell, A. (2017). Comprehensive Program to Produce Fair and Impartial Policing. USA: Springer International Publishing, p. 90. 62 11 CCR § 999.224(a)(7). 45 objectively reasonable apprehension of danger under the circumstances and not base their decision to conduct a pat search on any perceived individual characteristics. Reasonable suspicion to conduct a pat search is different than reasonable suspicion to detain. The scope of the pat search is limited only to a cursory or pat down search of the outer clothing to locate possible weapons. Once an officer realizes an object is not a weapon, or an object that can be used as a weapon, the officer must move on. • Probable Cause to Arrest: under the Fourth Amendment to the United States Constitution, arrests must be supported by probable cause. Probable cause to arrest is a set of specific facts that would lead a reasonable person to objectively believe and strongly suspect that a crime was committed by the person to be arrested. C. Model Policy Language for Limited Circumstances in which Characteristics of an Individual May Be Considered • [Agency] members may only consider or rely on characteristics listed in a specific description of a suspect, victim, or witness based on trustworthy and relevant information that links a specific person to a particular unlawful incident. • Except as provided above, [agency] officers shall not consider personal characteristics in establishing either reasonable suspicion or probable cause. D. Model Policy Language for Encounters with Community • To cultivate and foster transparency and trust with all communities, each [agency] member shall do the following when conducting pedestrian or vehicle stops or otherwise interacting with members of the public, unless circumstances indicate it would be unsafe to do so: o Be courteous, professional, and respectful. o Introduce themselves to the community member, providing name, agency affiliation, and badge number. [Agency] members should also provide this information in writing or on a business card.63 o State the reason for the stop as soon as practicable, unless providing this information will compromise officer or public safety or a criminal investigation. o Answer questions that the individual may have about the stop. o Ensure that a detention is no longer than necessary to take appropriate action for the known or suspected offense and [agency] member convey the purpose of any reasonable delays. 63 President’s Task Force on 21st Century Policing. (2015). Final Report of the President’s Task Force on 21st Century Policing. Washington, DC: Office of Community Oriented Policing Services, p. 27. Available at http://elearning-courses.net/iacp/html/webinarResources/170926/FinalReport21stCenturyPolicing.pdf (identified as recommendation 2.11, with accompanying Action Item 2.11.1 for promoting effective crime reduction while building public trust). 46 • All [agency] personnel, including dispatchers and non-sworn staff, shall not use harassing, intimidating, derogatory, or prejudiced language, including profanity or slurs, particularly when related to an individual’s actual or perceived individual characteristics. • Dispatchers and sworn personnel shall be aware of and take steps to curb the potential for bias by proxy in a call for service. • Officers should draw upon their training and use their critical decision-making skills to assess whether there is criminal conduct and to be aware of implicit bias and bias by proxy when carrying out their duties. • All [agency] personnel, including dispatchers and non-sworn personnel, shall aim to build community trust through all actions they take, especially in response to bias-based reports. E. Model Policy Language for Training • The [agency] will ensure that, at a minimum, all officers and employees are compliant with requirements regarding bias-free policing training. • The [agency] will ensure that management includes a discussion of its bias-free policing policy with its officers and staff on an annual basis. • [Agency] officers should be mindful of their training on implicit bias and regularly reflect on specific ways their decision-making may be vulnerable to implicit bias. F. Model Policy Language for Data Collection and Analysis • As required by the California Racial and Identity Profiling Act of 2015, [agency] is required to collect data on: (a) civilian complaints that allege racial and identity profiling and (b) perceived demographic and other detailed data regarding pedestrian and traffic stops. The data to be collected for stops includes, among other things, perceived race or ethnicity, approximate age, gender, LGBT identity, limited or no English fluency, or perceived or known disability, as well as other data such as the reason for the stop, whether a search was conducted, and the results of any such search. All agencies must report this data to the California Department of Justice. • The [agency] should regularly analyze data, in consultation with [academics, police commissions, civilian review bodies, or advisory boards], to assist in identifying practices that may have a disparate impact on any group relative to the general population. G. Model Policy Language for Accountability and Adherence to the Policy • All [agency] personnel, including dispatchers and non-sworn personnel, are responsible for understanding and complying with this policy. Any violation of this policy will subject the member to remedial action. o Types of remedial action should be outlined. 47 • All [agency] personnel, including dispatchers and non-sworn personnel, shall not retaliate against any person who complains of biased policing or expresses negative views about them or law enforcement in general. • All [agency] personnel, including dispatchers and non-sworn personnel, share the responsibility of preventing bias-based policing. Personnel shall report any violations of this policy they observe or of which they have knowledge. o Processes and procedures for reporting violations should be included. H. Model Policy Language for Supervisory Review • Supervisors shall ensure that all personnel under their command, including dispatchers and non-sworn personnel, understand the content of this policy and comply with it at all times. o Supervisory processes and procedures for monitoring should be included. • Any employee who becomes aware of any instance of bias-based policing or any violation of this policy shall report it in accordance with established procedure. • Supervisors who fail to respond to, document, or review allegations of bias-based policing will be subject to remedial action. o Types of remedial action should be outlined. o Supervisor processes and procedures for review should be included. Wave 1 Agency Bias-Free Policing Policy Review This year, the Board undertook a review of the bias-free policing or equivalent policies for all eight Wave 1 agencies. The matrix below summarizes the Board’s review of the most recent policies the Department obtained, based on the best practices outlined in the 2019 RIPA Board Report. Following the matrix is a more detailed review of each agency’s bias-free policing policy and related policies that contain relevant information. In the 2019 Report, the Board recommended various best practices to assist agencies with having clear, thoughtful, and robust bias-free policing policies. To that end, the Board reviewed the factors below. First, the Board assessed whether the policy was clear about the agency’s prohibition against bias- based policing and whether that commitment was furthered by having a stand-alone policy. Additionally, the Board reviewed whether the policy defined bias-based policing and explained in what limited circumstances personal characteristics may be considered. Next, the Board evaluated whether the policy was accessible to the public and whether the policy discussed guidelines according to which agency members should interact with the community. The Board also assessed whether the policy included a component on training related to racial and identity profiling. Lastly, the Board evaluated the accountability built into the policy by looking at whether the policy discussed analysis of data collected and supervisory review. In its review, the Board was not expecting each agency to exactly follow the above-mentioned model language. Instead, the Board looked for instances where the concepts above were incorporated into the policies. These recommendations represent an accumulation of best practices identified by the United States Department of Justice (USDOJ) and other relevant empirical research conducted by well-regarded 48 organizations, including the Police Executive Research Forum (PERF),64 the International Association of Chiefs of Police (IACP),65 the Vera Institute,66 Fair and Impartial Policing,67 Stanford SPARQ,68 and the Center for Policing Equity (CPE).69 The Department shared this review with the subject LEAs to ensure accuracy before including this information in the report. The RIPA Board encourages all Wave 1 agencies to re-examine their policies. The Policy Review that follows may assist agencies in identifying areas of opportunity to incorporate the best practices outlined in the Board’s 2019 report and the aforementioned model language. Uses Concrete Stand-Alone Definitions of Component on Limited Wave 1 Bias-Free Clearly Easily Bias-Free Policing Circumstances in which Agency Policing Written? Accessible? and/or Racial & Characteristics of Individual Policy? Identity May Be Considered? Profiling? San Francisco ü ü ü ü ü PD CHP û ü û ü ü Los Angeles ü ü ü ü ü PD Riverside ü ü û ü ü Sheriff San Bernardino ü ü û û û Sheriff San Diego ü ü û ü û PD San Diego ü ü ü û ü Sheriff Los Angeles û ü û û û Sheriff 64 Police Executive Research Forum (PERF). Information available at https://www.policeforum.org/. 65 International Association of Chiefs of Police (IACP). Information available at https://www.theiacp.org/. 66 The Vera Institute of Justice. Information available at https://www.vera.org/. 67 Fair and Impartial Policing. Information available at https://fipolicing.com/. 68 Stanford SPARQ. Information available at https://sparq.stanford.edu/. 69 Center for Policing Equity (CPE). Information available at http://policingequity.org/. 49 Component on Component Component on Component Wave 1 Racial and Requiring Supervisory Encounters with on Data Agency Identity Profiling Account- Review? Community? Analysis? Training? ability? San Francisco ü û ü ü ü PD CHP ü ü ü ü ü Los Angeles ü û û ü ü PD Riverside û ü û ü û Sheriff San Bernardino ü ü û û û Sheriff San Diego û û û ü û PD San Diego û û û û û Sheriff Los Angeles û û û ü û Sheriff San Francisco PD: The San Francisco Police Department is in the process of revising Department General Order 5.17.70 The information in the above chart is from a review of the current policy, which was revised in May 2011. The 2011 policy, which is available in English on the SFPD website71 mentions equal protection and Fourth Amendment laws and contains a definition of biased policing. In line with the Board’s best practice recommendations, it includes a component on the limited circumstances in which characteristics of individuals may be considered, as well as a component on communication with the community to prevent perceptions of biased policing. However, the policy does not contain a 70 In updating its anti-bias policy, the SFPD gathered various stakeholders from the community and local government, including the San Francisco Police Commission and the San Francisco Department of Police Accountability, to help draft the soon to be approved policy. Other law enforcement agencies should consider a similar approach to improve community and law enforcement relations. 71 See San Francisco Police Department. (2011). General Order 5.17: Policy Prohibiting Biased Policing [PDF file]. Available at https://www.sanfranciscopolice.org/sites/default/files/2018- 11/DGO5.17%20Policy%20Prohibiting%20Biased%20Policing.pdf. 50 component on racial and identity profiling training. It includes components for accountability and supervisory review. A separate policy, San Francisco Administration Code, section 96A.3, mandates SFPD to conduct analysis and reporting of collected data. Quarterly reports with the data analysis, including an executive summary, are available on the agency’s website. CHP: The California Highway Patrol does not have a stand-alone bias-free policing policy. Relevant content is integrated into the Enforcement Policy Manual and is additionally reflected in the Drug Programs Manual; neither of these manuals is available online. The Enforcement Policy Manual includes information on the requirements under current state and federal law. CHP policies define racial and identity profiling, as well as probable cause, consent, and reasonable suspicion. They include a component on the limited circumstances in which characteristics of individuals may be considered, as well as a component on encounters with the community. Annual cultural awareness training is provided to all employees and includes training on racial profiling; an eight-hour classroom-training course is alternated with an online refresher course every odd-numbered calendar year. The policies include components for the analysis of the collected data, accountability, and supervisory review. LAPD: The Los Angeles Police Department has a three-paragraph, stand-alone Policy Prohibiting Biased Policing that is clearly written and available in English on the LAPD website.72 The policy was updated in November 2019, expanding protected classes to include immigration or employment status, language fluency, and homeless circumstance. The policy defines bias-free policing. It includes a component on the limited circumstances in which characteristics of individuals may be considered. Furthermore, it designates failure to comply as an act of serious misconduct and requires employees to report violations of the policy. Related content is included in other policy sections, including encounters with the community. Supervisory review is addressed in a separate section of the Department Manual. Section 4/202.2 – Automated Field Data Reports (AFDR)/Completion and Tracking outlines officers’ responsibilities for completing AFDRs and describes supervisors’ responsibilities for: • reviewing AFDRs promptly to ensure that officers are properly completing the AFDR per the AFDR Completion Guide and Supervisor AFDR Completion Guide; • editing or directing the completing officer to revise the narrative portions of the AFDR, when appropriate; • ensuring that a legal basis for the detention and search (if applicable) is adequately articulated in the narrative; and, • ensuring that no identifying characteristics of the person(s) being stopped or the officer(s) involved are listed. Watch Commanders and Commanding Officers’ responsibilities related to AFDR are also specified. The LAPD policy does not include a component on racial and identity training. However, LAPD provided to the Board a ten-page Police Training and Education – 2019 Biased Policing Reduction 72 See Los Angeles Police Department. (2019). 2019 2nd Quarter Manual. Available at http://lapdonline.org/lapd_manual/volume_1.htm#345. 51 Strategy document that includes detailed information about current training courses required of officers, supervisors, and command staff. The LAPD policy does not include a component on data analysis. LAPD did, however, share a document, Efforts to Reduce the Number of Biased Policing Complaints Report, which outlines the LAPD’s data analysis efforts. In a letter to the Department, dated December 2, 2019, the LAPD provided additional details about data analysis by a Steering Committee that meets every four weeks. The letter also describes a Stop Data Dashboard that the LAPD is developing to provide commanding officers insight into the types of stops being conducted, reasons for stops, searches conducted, and actions taken by officers in the field. Riverside Sheriff: The Riverside County Sheriff’s Department has a clearly written stand-alone73 policy that was last revised October 7, 2019. The policy is not available online. It defines bias-based policing and includes a component on the limited circumstances in which characteristics of individuals may be considered. There is no component on encounters with the community. The policy includes a component on officer training and encourages members to familiarize themselves with racial and cultural differences if they have not yet received training. The policy does not include a component on data analysis; it does delineate, however, what data is collected for RIPA. The policy requires members to be responsible for reporting any biased-based policing they suspect or have knowledge of and encourages members to intervene whenever they see bias-based actions. The policy does not address supervisory review. San Bernardino Sheriff: The San Bernardino County Sheriff’s Department has a clearly written two- sentence, stand-alone policy prohibiting biased policing. This policy is not available on the agency’s website; the agency submitted it to the RIPA Board. It does not include definitions of bias-free policing or racial and identity profiling nor a component on the limited circumstances in which characteristics of individuals may be considered. The policy contains a component on interaction with the public and states that the Sheriff’s Department must provide initial and continuing training in community relations. The policy discusses data collection but does not address analysis, accountability, or supervisory review. San Diego PD: The San Diego Police Department has a clearly written stand-alone policy that was last revised in 2015. The policy is available in English on the SDPD website.74 The policy defines bias-based policing. It does not include recommended components on the limited circumstances in which characteristics of individuals may be considered, communication with the community, training, data analysis, or supervisory review. SDPD requires members to make every effort to prevent and report bias-based policing by fellow members. 73 A private corporation provides Riverside’s policy through a paid subscription service offered to law enforcement agencies around the country. 74 See San Diego Police Department. (2016). Policy Manual [PDF file], p. 35. Available at https://s3.amazonaws.com/themis.datasd.org/policies_procedures/Policies/Complete%20Policy%20Manual.pdf 52 San Diego Sheriff: The San Diego County Sheriff’s Department has a clearly written, seven-paragraph section in the Procedures Manual concerning their stand-alone policy, which was last revised in August 2018. The policy and procedures are available in English on their website.75 The policy mentions Fourth Amendment laws and refers to the updated definition of racial or identity profiling, but the definition is not included in the policy itself. It contains a component on the limited circumstances in which characteristics of individuals may be considered, but does not address encounters with the community, training, accountability, or supervisory review. The policy discusses RIPA data collection, but not data analysis. Los Angeles County Sheriff: The Los Angeles County Sheriff’s Department (LASD) does not have a stand-alone policy; the policy is integrated into the Policy of Equality. Additionally, the LASD’s Constitutional Policing Policy emphasizes the Department’s commitment to equal protection without bias. It is clearly written and available in English on the Sheriff’s website.76 The policy does not include definitions of bias-free policing or racial and identity profiling. The policy does not include components on the limited circumstances in which characteristics of individuals may be considered, encounters with the community, training, or analysis of the collected data. It contains general supervisory review statements and refers to an Equity Oversight Panel that reviews each Equity Unit internal complaint investigation and the effectiveness of the policies and procedures. The Affirmative Action unit receives and processes external complaints of discrimination, harassment, and retaliation, who then forwards the complaints to the Equity Unit for investigation and resolution. Vision for Future Reports In the coming years, the Board hopes to review the bias-free policing policies of the Wave 2 and Wave 3 agencies as they begin to submit stop data. It will also seek to incorporate any revisions or updates agencies may make to their bias-free policing policies in its review. Future reports will also include any changes to best practices that may inform law enforcement agencies’ bias-free policing policies and practices. 75 See San Diego County Sheriff’s Department. (2018). Policy and Procedure Manual [PDF file]. Available at https://www.sdsheriff.net/documents/pp/pp-20160321.pdf. 76 See Los Angeles County Sheriff’s Department. (2018). Policy and Ethics. In Manual of Policy and Procedures. Available at http://shq.lasdnews.net/shq/mpp/3-01.pdf; Los Angeles County Sheriff’s Department. (2017). Miscellaneous Line Procedures. In Manual of Policy and Procedures. Available at http://shq.lasdnews.net/shq/mpp/5-09.pdf. 53 Calls for Service and Bias by Proxy In its 2019 Report, the RIPA Board introduced the topic of bias by proxy in the context of calls for service. Bias by proxy occurs in a call for service “when an individual calls the police and makes false or ill-informed claims about persons they dislike or are biased against.”77 Because calls for service are the most common way in which law enforcement officers make contact with the public, it is critical that law enforcement agencies have policies and training in place about how to prevent bias by proxy when responding to a call for service. Best Practices for Responding to Biased-Based Calls for Service We were unable to find any law enforcement agency in California that had a policy that addresses the circumstances in which members of the public make bias-based calls for service.78 The Board reviewed evidence-based best practices for responding to bias-based calls for service and identified the following best practices: • Agencies should have a policy detailing how sworn personnel and dispatchers should respond to bias-based reports, reports regarding bias, or bias by proxy from the community. This policy could be a stand-alone policy or integrated into the bias-free policing policy. • An agency policy covering biased-based calls for service should include: o How an officer should identify a biased-based call for service. § It should first instruct the officer to determine whether there is evidence of criminal misconduct or if there is a need to engage in a community caretaking function. § It should include clear direction on next steps with respect to the caller and subject of the call (see below) if an officer determines that there is no criminal conduct or no need to conduct a well-being check. § It should allow officers to respond to the area and independently assess the subject’s behavior from a distance. If no suspicious criminal behavior is observed, then the officer can report the call to dispatch as “unfounded.” o How sworn personnel and dispatchers should interact with the community member who has made a bias-based call for service. § It should detail ways personnel can courteously explore if the call is bias-based and concerns an individual’s personal characteristics (e.g., call regarding a 77 Fridell, A. (2017). A Comprehensive Program to Produce Fair and Impartial Policing. In Producing Bias-Free Policing. Springer, p. 90. 78 We are aware that the San Francisco Police Department is in the process of incorporating bias by proxy into the new draft of its anti-bias policing policy. If adopted, we believe this would be the first policy in California, certainly of a major police department, to incorporate concepts of bias by proxy into its department general orders. 54 person of color walking in the “wrong neighborhood”) or if there are specific behaviors that warrant a call for police response. If the complainant can offer no further, concrete information, the complainant may be advised that the shift supervisor will be in contact at the first opportunity. • Specifically, dispatchers could have a series of questions or a flexible script, which enables them to ask questions and explore whether there are concrete, observable behaviors that form the basis of the suspicious activity or crime the caller is reporting. Is the person looking into cars, checking doors, casing homes, etc.? What specific crime or activity does the person claim to be witnessing?79 § If a call turns out to be a bias-based call for service, the shift supervisor may follow up with the caller to let them know that they found no suspicious or criminal activity. This way of “closing the call” may help educate callers about appropriate calls for service and possibly alleviate dispatching calls that have no merit, while serving to build trust between police and the community. o How an officer should interact with a community member who is the subject of a bias- based call. § It should detail methods on how to approach the subject of a bias-based call in a manner that respects their dignity and does not alarm them, but informs them about the reason that the officer is on scene. § It should include methods to account for situations in which the responding officer encounters both the caller and the subject of a potential bias-based call at the scene. • Such methods should include de-escalation, respectful listening, and procedural justice techniques to ensure the scene is safe, the parties have an opportunity to communicate, and the officer has the opportunity to explain why no violation has occurred. o How the shift supervisor should interact with the caller: § It should detail how the shift supervisor can explain that the agency does not respond to calls for service based on an individual’s personal characteristics and 79 One illustrative example is what Nextdoor, a neighborhood communication platform, has developed in collaboration with community groups, local law enforcement, academic experts, and neighbors to try to prevent racial profiling and make crime reporting more useful to neighbors and law enforcement. Nextdoor has the following tips: “1) Focus on behavior. What was the person doing that concerned you, and how does it relate to a possible crime?; 2) Give a full description, including clothing, to distinguish between similar people. Consider unintended consequences if the description is so vague that an innocent person can be targeted.; and 3) Don’t assume criminality based on someone’s race or ethnicity. Racial profiling is expressly prohibited.” See Nextdoor. (2017). Preventing Racial Profiling on Nextdoor. Available at http://us.nextdoor.com/safety/preventing-profiling-approach. 55 that lawful activities are not more suspicious because of the individual’s personal characteristics. § It should detail ways the shift supervisor can educate the caller on the agency’s bias-free policing policy and philosophy and explain that officers respond to behaviors/actions of individuals that appear suspicious, threatening, illegal, etc., and not to hunches or situations based on an individual’s personal characteristics. § In the case of a call for service that is based on a caller's suspicion that an individual present in the jurisdiction is an undocumented immigrant, the supervisor could inform the caller that California law enforcement agencies are not responsible for enforcing federal immigration law, as provided for in the California Values Act (Cal. Gov. Code, §§ 7284 et seq.). These interactions should be documented by the supervisor. • Agencies should have a training for officers and dispatchers that covers responding to bias- based calls for service. It should include: o Foundational instruction on how poor or inadequate responses to such calls can impair the agency’s legitimacy and undermine other agency efforts to build community trust and communication. o How to be mindful of their training on implicit bias and regularly reflect on whether such bias is affecting a caller’s decision-making (e.g., assuming a higher or lower threat level presented by an individual based upon his or her race, gender, or other personal characteristics). o How to assess a call for bias-based motivations. o How information regarding a call for service should be relayed without including biased assumptions. o How to collect enough information necessary to verify reasonable suspicion of criminal activity. o How to record and track any bias-based call in the agency’s tracking systems. o How on-scene responses to calls for service may require officers to apply de-escalation, communications, and procedural justice techniques. o The subject of biased-based calls for service should also be included in supervisor and leadership training as desktop exercises so that attendees grasp the challenge bias- based calls present to the agency’s overall mission. It would be beneficial for dispatchers and officers to jointly attend training on calls for service so that the training can address the intersecting roles and responsibilities of both positions in dealing with bias-based calls for service. The Board also recommends that dispatchers go on a ride-along with a field officer as part of their training, and that field officers do a sit-along in the dispatch center so that 56 each can build a better understanding of what the other job entails. This will open up the lines of communication between the two positions and enable them to better handle not only calls rooted in bias by proxy, but all dispatch calls generally. Vision for Future Reports In the coming years, the Board hopes to examine model language to incorporate into policies regarding bias-based calls for service and any training on this topic. In addition, the Board hopes to assess best practices for law enforcement agency responses to calls for service that may require special training or assistance from a Critical Intervention Team to address mental health issues. 57 Civilian Complaints: Policies and Data Analyses Introduction California law requires “[e]ach department or agency in this state that employs peace officers shall establish a procedure to investigate complaints by members of the public against the personnel of these departments or agencies, and shall make a written description of the procedure available to the public.”80 Police agencies have been submitting this complaint information to the Department since 1981. In 2016, RIPA required all law enforcement agencies to include the numbers of complaints alleging racial or identity profiling.81 State law also requires agencies to include the number of complaints that reached the dispositions of “sustained,” “exonerated,” “not sustained,” and “unfounded.” Once submitted, the Department then disaggregates and analyzes the data for inclusion in the Board’s annual report.82 Below, the Board provides an overview of the civilian complaint data submitted by agencies in 2018; analyzes complaints submitted to the Department from 1981 to the present; and engages in a more focused examination of civilian complaint data provided by the agencies required to submit stop data. The Board has also reviewed the civilian complaint policies of the Wave 1 agencies and provides recommendations for agencies to consider in assessing their civilian complaint policies and procedures. Overview of Civilian Complaint Data Submitted by All Reporting Agencies The most recent data on civilian complaints submitted to the Department are from 2018. In that year, 702 agencies that employ peace officers in California reported 16,525 civilian complaints to the Department.83 The agencies report the total number of complaints in 3 categories: non-criminal, misdemeanor, and felony. We learned that a majority of the complaints (15,635, or 94.6%) alleged conduct that was non-criminal in nature. Complaints alleging behavior that constituted a misdemeanor offense accounted for 3.5 percent (576) of the complaints, and felony allegations represented 1.9 percent (314) of complaints. Agencies also report the total number of racial profiling complaints and further break down those complaints by type.84 Currently, law enforcement agencies submit data to the Department regarding 80 Pen. Code, § 832.5, subd. (a)(1). 81 Pen. Code, § 13012, subd. (a)(5)(A)(iii). 82 Pen. Code, §§ 13012, subds. (a)(5)(C), (c). 83 Some of the 702 agencies reported zero civilian complaints. Civilian complaint data includes complaints against both peace officers and non-peace officer employees of the agency, as well as complaints against custodial officers and those that take place in a custodial setting (e.g., complaints by inmates). As noted below, the Board recommends that civilian complaints be disaggregated to distinguish these differing types of complaints. 84 Though racial profiling is against the law, the form to report civilian complaints against peace officers does not delineate the categories of racial profiling complaints (e.g. non-criminal or misdemeanor). 58 racial and identity profiling complaints based on nine identity groups: mental disability, physical disability, sexual orientation, gender identity/expression, religion, age, gender, race/ethnicity, and nationality. This year’s data showed that complainants alleged an element, or elements, of racial or identity profiling in 1,193 (7.2%) of the total number of complaints submitted in 2018. Figure 14, below, displays the total number of allegations of racial and identity profiling (1,432) reported to the Department in 2018; note that this exceeds the total number of complaints (1,193) because complainants may allege profiling based on more than one identity group within the same complaint. For example, a civilian may file a complaint alleging they experienced profiling based on their religion and gender. This example would count as one complaint with two types of alleged racial and identity profiling. Thus, the numbers in the figure show the number of allegations of different types of profiling rather than the total number of complaints. Figure 14. Profiling Allegations Submitted to All California Agencies, Reported by Type, 2018 Total Allegations of Racial and Identity Profiling Including Non-RIPA-Reporting Agencies Mental Disability Physical Disability Sexual Orientation (40) 3% (67) 5% (60) 4% Gender Identity Expression (55) 4% Religion (48) 3% Total Age Allegations (22) 1% Reported: 1,432 Gender (58) 4% Nationality (40) 3% Race and Ethnicity (1042) 73% 59 Analysis of Civilian Complaint Data Submitted by Agencies Subject to RIPA In total, 453 agencies subject to RIPA’s stop data reporting requirements submitted information regarding the civilian complaints they received for 2018.85 This includes all city and county law enforcement agencies, the California Highway Patrol, and the law enforcement agencies of the University of California, California State Universities, California Community Colleges, and K-12 school district police departments. Civilian Complaints for All Agencies Required to Report Stop Data The 453 agencies that are subject to RIPA reported 10,044 civilian Key Terms complaints. Most complaints alleged noncriminal conduct (9290, or 92.5%), followed by complaints for conduct that constitutes a Reported: the number of civilian misdemeanor offense (523, or 5.2%); felony complaints were the complaints reported for the calendar least common (231, or 2.3%). Of the complaints that reached a year (January 1 – December 31). disposition in the 2018 calendar year, 919 (10.8%) were sustained, Sustained: investigation disclosed 2,308 (27.2%) were exonerated, 1094 (12.9%) were not sustained, and 4167 (49.1%) were unfounded. As stated above, not every sufficient evidence to prove truth of complaint reached a disposition during the same year reported; allegation in complaint by therefore, it is possible that some complaints that appeared in the preponderance of evidence. 2018 disposition categories were reported in 2017 or earlier. Exonerated: investigation clearly Of the 453 agencies subject to RIPA, 76 (16.8%) indicated they established that employee’s actions received no civilian complaints during the 2018 calendar year. The that formed basis of allegations in remaining 377 (83.2%) reported they received one or more civilian complaint were not a violation of law complaints; within this category, 134 (35.5%) agencies reported one or agency policy. or more civilian complaints alleging racial or identity profiling. These 134 agencies reported 896 complaints alleging racial or identity Not sustained: investigation failed to profiling. disclose sufficient evidence to clearly prove or disprove complaint’s Of the 751 racial and identity profiling complaints that reached a allegation. disposition in 2018, 10 (1.3%) were sustained, 99 (13.2%) were not sustained, 91 (12.1%) were exonerated, and 551 (73.4%) were Unfounded: investigation clearly determined to be unfounded. established that allegation is not true. Figure 15 below displays the 1,081 allegations of racial or identity Pending: number of complaints profiling filed in 2018 with the 134 agencies subject to RIPA that reported in the current year that are reported receiving at least one such complaint. The type of profiling currently awaiting disposition. alleged further breaks down these complaints by race or ethnicity, 85 Data for the full set of agencies that reported civilian complaint information in 2018, including agencies not subject to RIPA's stop data collection requirements (e.g., Probation Departments and most California state law enforcement agencies) is available on the Department's OpenJustice Data Portal: https://openjustice.doj.ca.gov/data. 60 nationality, physical or mental disability, sexual orientation, gender identity or expression, religion, age, and gender.86 Figure 15. Profiling Allegations Filed with RIPA Agencies, Reported by Type, 2018 Total Racial and Identity Profiling Allegations Reported Religion, 15, 1% Nationality, 37, 4% Gender, 51, 5% Age, 21, 2% Gender Identity Expression, 25, 2% Mental Disability, 30, 3% Total Allegations Sexual Orientation, 24, Reported: 2% 1,081 Physical Disability , 34, 3% Race and Ethnicity, 844, 78% Nationality Gender Religion Age Gender Identity Expression Mental Disability Sexual Orientation Physical Disability Race and Ethnicity Agency-Level Data Snapshot: 2018 Civilian Complaints for Wave 1 Agencies As a starting point for its analysis of agency-level data, the Board looked at the civilian complaint data for all Wave 1 agencies. Table 5 provides information on the total number of complaints reported by Wave 1 agencies for sworn personnel, including custodial officers; the number of complaints alleging racial or identity profiling; and the number of sworn personnel each agency employed in 2018. 86 Just as with Figure 1, the number of allegations of profiling in Figure 15 (1,081) exceeds the number of total profiling complaints (896) because one complainant may allege profiling based on multiple identities. 61 Table 5: Wave 1 Agency Complaints and Sworn Personnel Agency Total Profiling Sworn Personnel Complaints Allegations Reported Reported Los Angeles Police 1,907 274 9,974 Department (14%) Los Angeles County Sheriff’s 986 67 9,426 Department (6.7%) California Highway Patrol 287 35 7,286 (12%) San Diego County Sheriff’s 9 1 2,572 Department (11%) San Francisco Police 678 21 2,306 Department (3%) San Bernardino County 104 35 2,018 Sheriff’s Department (33%) Riverside County Sheriff’s 46 4 1,795 Department (9%) San Diego Police Department 74 15 1,731 (20%) Note: The percentages in the Profiling Allegations Reported column display the proportion of the Total Complaints Reported column that alleged racial or identity profiling for each agency. Figures 15 and 16 display the number of total complaints reported (Figure 15) as well as the total number of racial and identity profiling allegations reported (Figure 16) for Wave 1 agencies across the three years the agencies have been required by RIPA to submit expanded civilian complaint data to the Department. The total number of civilian complaints for all Wave 1 agencies was 3,904 in 2016, 3,679 in 2017 (a 5.8 percent decrease from 2016), and 4,091 in 2018 (an 11.2 percent increase from 2017, and a 4.8 percent increase from 2016). 62 Half of the Wave 1 agencies experienced an increase in the number of civilian complaints reported between 2017 and 2018, and the other half experienced a decrease. The agency that experienced the largest percentage increase in 2018 was the San Diego County Sheriff’s Department (SDSD), with a 50 percent increase. To put this increase in context, it is important to know that relative to the rest of the Wave 1 agencies, this agency experienced very low numbers of complaints across the three years covered in Figure 15, making it more susceptible to large percentage changes from year to year. Of the other seven Wave 1 agencies, the San Francisco Police Department (SFPD) had the largest increase in reported complaints from 2017 to 2018 (28.7% increase). The agency that experienced the highest percentage decrease in reported complaints from 2017 to 2018 was the San Bernardino County Sheriff’s Department (SBSD), which saw a 41 percent decrease from their number of complaints in 2017 (78) to 2018 (46). Figure 15. Wave 1 Complaints Reported by Year (2016-2018) Total Complaints Reported San Francisco Police Department San Diego Police Department San Diego County Sheriff's Department San Bernardino County Sheriff's Department Riverside County Sheriff's Department Los Angeles Police Department Los Angeles County Sheriff's Department California Highway Patrol 0 250 500 750 1000 1250 1500 1750 2000 San Los Angeles Riverside San Diego San California Los Angeles Bernardino San Diego County County County Francisco Highway Police County Police Sheriff's Sheriff's Sheriff's Police Patrol Department Sheriff's Department Department Department Department Department Department 2016 349 920 1997 70 175 13 129 251 2017 308 828 1729 78 106 6 97 527 2018 287 986 1907 46 104 9 74 678 Figure 16 displays the total number of racial and identity profiling allegations reported by Wave 1 agencies for years 2016 through 2018. The total number of racial and identity profiling allegations was 129 in 2016, 371 in 2017 (a 187.6 percent increase from 2016), and 452 in 2018 (a 21.8 percent increase from 2017, and a 250.4 percent increase from 2016). Both 2017 and 2018 saw stark increases in the number of racial and identity profiling allegations reported by Wave 1 agencies in comparison to 2016. However, 2016 was the first year that agencies were required to track the annual number of racial and identity profiling allegations and report it to the Department. As a result, the comparatively low number of racial and identity profiling allegations reported in 2016, compared to subsequent 63 years, may be the result of the learning curve of agencies having to collect the data in a different way from the past. Of the eight agencies in Figure 16, five experienced an increase in the number of reported racial and identity profiling civilian allegations between 2017 and 2018, while the other three experienced a decrease. The LASD had the largest relative increase: it reported 31 racial and identity profiling allegations in 2017 and more than double in 2018 at 67 (a 116.1 percent increase). On the other end of the spectrum, the SFPD had the second largest increase in total civilian complaints reported from 2017 to 2018 and the largest percentage decrease in the number of reported racial and identity profiling allegations from 2017 to 2018 (48.8%). Figure 16. Wave 1 Racial and Identity Complaints Reported by Year (2016-2018) Total Racial and Identity Profiling Complaints Reported San Francisco Police Department San Diego Police Department San Diego County Sheriff's Department San Bernardino County Sheriff's Department Riverside County Sheriff's Department Los Angeles Police Department Los Angeles County Sheriff's Department California Highway Patrol 0 25 50 75 100 125 150 175 200 225 250 275 San Los Angeles Riverside San Diego San California Los Angeles Bernardino San Diego County County County Francisco Highway Police County Police Sheriff's Sheriff's Sheriff's Police Patrol Department Sheriff's Department Department Department Department Department Department 2016 22 1 52 1 19 3 8 23 2017 24 31 215 7 39 1 13 41 2018 35 67 274 4 35 1 15 21 Factors to Consider in Analyzing Data When reviewing the data presented above, it is important to recognize that the reporting policies and practices of the agencies may account for some disparities in the number of complaints submitted by agencies of similar size. In other words, the fact that one agency has documented or reported disproportionately more or fewer complaints than another may be the product of factors unrelated to the agency’s performance or community satisfaction with the agency. The Board has discussed various factors that may result in differences in the numbers of complaints reported across agencies, including inconsistency in the complaint processes across the state and accessibility issues. Below is a brief discussion of several factors that likely impact disparities in the number of complaints between agencies as well as disparities in the number of complaints submitted by all agencies in California over a multi-year period. 64 Lack of Uniformity Regarding What Constitutes a “Civilian Complaint” and How to Quantify Complaints First, disparities in the numbers of complaints documented, investigated, and reported by agencies may arise in part because the agencies in question do not necessarily share a common understanding of what counts as a “complaint.” Penal Code section 832.5 does not include a definition of “complaint” for reporting purposes, and there is no professional consensus within California on a definition. Factors to Consider When Defining a “Civilian Complaint” • Verbal complaints – whether there is a duty to document, investigate, and report. • Complaints – verbal or written – by arrested individuals. • Complaints by uninvolved third parties who witness misconduct. • Multiple complaints by third parties about one incident o Is every complaint logged or are all logged as one incident? • Is an officer required to self-report when verbally accused of racial profiling or other forms of biased policing? Instead, agencies in California have the discretion to adopt or develop various definitions and systems for handling civilian complaints. One might suspect, then, that an agency with a relatively narrow definition of a civilian complaint — such as submitting a completed civilian complaint form signed under penalty of perjury — would have fewer reported complaints than an agency that has a broader policy that also includes oral complaints that are later memorialized in writing. The lack of an agreed-upon definition or process for responding to complaints can contribute to wide differences in reported data, even if all agencies examined are acting in the utmost good faith. Even a brief consideration of the many ways community members might express dissatisfaction or allege misconduct will identify potential areas of disagreement. Consider the following: • Community Member A informs a Sergeant she knows that a patrol officer has regularly been running red lights without any apparent emergency. She adds, “I don’t want make out one of those citizen complaints, because I like that officer. But there are lots of children out here, and thought you might speak to him.” The allegations, if true, would violate agency policy and possibly traffic laws. Should this communication count as a “complaint” within Penal Code section 832.5? • Community Member B informs a Sergeant that an officer “roughed up” her neighbor’s teenage son. The teenager and his family state they do not wish to become involved “because we have to live in this neighborhood.” Should the allegation count as a “complaint” for reporting purposes? 65 • Community Member C is driving on her way home from work when she is pulled over by an officer. The officer checks Community Member C’s driver’s license and finds she has an outstanding arrest warrant for failure to appear at a court hearing. Upon arrest, Member C accused the officer of racial profiling. Does this allegation trigger the agency’s reporting, investigation, and retention requirements for civilian complaints? Should the accused officer be required to self-report the allegation, even if Community Member C does not take further action, such as completing a complaint form or otherwise making a more formal complaint? o Even if Community Member C did later submit a written statement that includes the racial profiling allegations, would all agencies treat the allegations as a civilian complaint, a defense to a criminal charge, an arrestee/prisoner grievance, or something else? • During an agency’s investigation of an excessive force complaint, a neighborhood witness tells the investigator that he witnessed the same officer use excessive force on a different neighbor last week. Should that new allegation of misconduct count as a second “civilian complaint” for reporting purposes, or would the agency treat the new allegation as part of the original investigation? Another factor related to the core concept of what constitutes a “civilian complaint” is how to accurately log such a complaint. For example, if 10 people witness an altercation between an officer and an individual at an event and submit written complaints about the incident to an agency, does the agency log 10 complaints or just one, because they all have to do with the same incident? Do all agencies accept complaints from third parties regarding interactions they observe, even though the third parties are not directly involved in interactions with the peace officer? With the emergence of social media, there is also the opportunity for law enforcement to consider accepting complaints from less formal means. Consider, for example, what might happen if an agency learned that a community member posted a video recording on the Internet that depicted apparent officer misconduct towards another community member. Would the agency consider the original posting a civilian complaint that must be logged, reviewed, and reported to the Department? What about additional comments following the original posting? What if one or more of those comments included separate allegations of misconduct by agency personnel? The Board raises these examples to illustrate why there may be disparities in reporting and to further urge law enforcement agencies to think about how the term “complaint” should be defined and/or expanded. Clear policies that address these questions will provide officers with direction that will hopefully standardize the civilian complaint processes within each agency as well as across California. A review of the complaint policies of the Wave 1 reporting agencies reveals that the term “civilian complaint” is not defined in any of these policies. The Los Angeles County Grand Jury, in a recent report on the civilian complaint process of several law enforcement agencies in Los Angeles County, suggested the following definition: 66 A complaint is an allegation by any person that a sworn officer or custodial employee of an agency, or the agency itself, has behaved inappropriately as defined by the person making the allegation. The person making the allegation is the complainant.87 As another example of a possible definition of “complaint,” the Los Angeles County Sheriff’s Department defines “personnel complaint” as “an external allegation of misconduct, either a violation of law or Department policy, against any member of the Department.” The National Association for Civilian Oversight of Law Enforcement (NACOLE) likewise suggests that the “types of complaints that should be investigated include allegations that, if proven true, would represent misconduct under the police department’s policies and procedures.”88 Even using one of these definitions, however, agencies may still vary regarding how to respond to a complaint, such as how to respond to verbal complaints, third-party complaints, or complaints reported by the officer who is the subject of the complaint. Lack of Uniformity Regarding How to Process Civilian Complaints Another factor that could explain an agency’s relatively low number of civilian complaints is an agency’s system for processing complaints and, in particular, the lack of a centralized repository for civilian complaints. For example, complaints that allege use of force may be reported directly to an Internal Affairs or Professional Standards unit within an agency, or to a Civilian Review Board, and may not be classified as civilian complaints. By contrast, complaints that allege verbal abuse or racial or gender identity slurs and not use of force may be processed and treated differently, through different investigative channels. Likewise, some complaints may be classified as “inquiries” or “adverse comments” and not logged as a reportable civilian complaint. Complaints may also be classified according to the level of review they are afforded, which may skew the numbers.89 And certain complaints, such as complaints of domestic violence involving officers, may be treated differently from complaints about an officer for interactions that occur while on duty. 87 Los Angeles Grand Jury Report, 2017-2018, p. 86. Available at http://www.grandjury.co.la.ca.us/pdf/2017- 2018%20los%20angeles%20county%20civil%20grand%20jury%20final%20report.pdf. 88 National Association for Civilian Oversight of Law Enforcement. (2016). What Types of Complaints Should Be Accepted? Available at https://www.nacole.org/complaints. 89 See, e.g., USDOJ, Civil Rights Division. (2016). Investigation of the Baltimore City Police Department, pp. 139, 141. Available at https://www.justice.gov/opa/file/883366/download (holding that “[a]ppropriately categorizing a complaint is critical because it affects which internal affairs component will investigate, the level of investigation undertaken, and the possible discipline imposed”; describing the Baltimore PD’s failure to consistently review how complaints are categorized in its internal affairs database, thereby vesting considerable discretion in supervisors; and finding that “supervisors frequently use this discretion to classify allegations of misconduct that result in minimal investigation”). 67 For example, in 2016, the USDOJ issued a report regarding its investigation of the Baltimore Police Department (Baltimore PD), finding that the Baltimore PD “failed to effectively investigate complaints alleging racial bias—often misclassifying complaints to preclude any meaningful investigation.”90 USDOJ uncovered only one complaint that that Baltimore PD classified as a racial slur in six years of complaint data. Yet a manual review of the complaints from the Baltimore PD revealed 60 additional complaints that alleged that officers used a racial slur; nonetheless, these complaints were misclassified as a lesser offense.91 Indeed, USDOJ found that a particular racial slur was misclassified 98 percent of the time.92 As the Baltimore PD exemplifies, how an agency classifies a civilian complaint – whether done intentionally or inadvertently – can skew the numbers of complaints reported, present an obstacle to the transparency that such data collection is designed to further, and make systematic analyses and comparisons across agencies difficult, if not impossible. In its recent review of the Sacramento Police Department (Sacramento PD), the Department noted that the Sacramento PD’s complaint intake procedure permitted complaints to be referred to either the employee’s supervisor or Internal Affairs and found that this system gave too much discretion for how personnel complaints were handled in the first instance. As a result, the Department recommended that all complaints be referred to Internal Affairs for processing, and that Internal Affairs should serve as the repository for all complaints, regardless of origin or level of severity.93 The lack of a centralized information source for complaints, which is not unusual based on our review of complaint practices, could lead to underreporting of civilian complaints, which may in turn explain disparities in reporting. Another recommendation the Department made in its review of the Sacramento PD was to establish a complaint classification system that would categorize complaints according to the severity of the offense. In reviewing the Sacramento PD complaint policies and procedures, the Department noted 90 Ibid, p. 47. 91 Ibid, p. 62. See also p. 66 (“Even when individuals successfully make a complaint alleging racial bias, BPD supervisors almost universally misclassify the complaint as minor misconduct—such as discourtesy—that does not reflect its racial elements.”), and p. 68 (As a result of misclassification, “[Baltimore] PD does not investigate the frequent allegations of race-related misconduct made against its officers and has no mechanism to track allegations to correct discriminatory policing where it occurs). 92 Ibid, p. 69 (“Failing to recognize the potential for racial discrimination in the use of a racial epithet is difficult to attribute to a lack of training, policy guidance, or other systemic deficiency. This systemic misclassification of complaints, particularly when the classification is not difficult, indicates that the misclassification is because of the racial nature of the complaints.”), pp. 141-142 (finding that complaints were misclassified and sent to different track for review, for example, as “supervisor complaints,” which are not required to be investigated and that “[Baltimore] PD administratively closed 67 percent of supervisor complaints and sustained just 0.27 percent of them . . . . By administratively closing complaints, [Baltimore] PD investigators evade [Baltimore] PD policy that requires all complaints to be labeled as sustained, not sustained, exonerated or unfounded . . . . These administrative closures, combined with [Baltimore] PD’s failure to ensure that complaints are appropriately classified, undermine [Baltimore] PD’s system of accountability and contribute to the perception shared by officers and community members alike that discipline is inconsistent and arbitrary.”). 93 California Department of Justice. (2019). Sacramento Police Department Report and Recommendations. California: Office of the Attorney General, p. 69. Available at https://oag.ca.gov/system/files/attachments/press- docs/spd-report.pdf. 68 that Sacramento PD identified four types of complaint classifications: (1) inquiries; (2) Office of Public Safety Accountability (OPSA) complaints; (3) civilian complaints; and (4) Department complaints. Inquiries or OPSA complaints were investigated informally, and did not trigger the same tracking and documentation requirements as civilian or Department complaints, which required documentation on a specified form, forwarding via the chain of command, a formal investigation, and tracking via an electronic database. Accordingly, the Department recommended that personnel complaints be tracked uniformly and classified by type of alleged misconduct, such as excessive use of force or racial bias.94 Likewise, the Los Angeles County Sheriff’s Department classifies complaints from members of the public as “service complaints” (“external communication of dissatisfaction with Department service, procedure or practice, not involving employee misconduct”) or “personnel complaints” (“an external allegation of misconduct, either a violation of law or Department policy, against any member of the Department”),95 which are governed by different procedures.96 These examples illustrate how agencies have differed in how they track complaints they receive; consequently, certain complaints alleging racial bias may not be processed as civilian complaints that are reported to the Department. Without a uniform system to accept, document, investigate, and report complaints, agencies may not only provide inaccurate or incomplete reporting data, but also blind themselves and limit their ability to respond to personnel or operational problems identified by the communities they serve. An agency’s ability to audit its complaint system to account for complaints received by a variety of means (e.g., complaints logged in separate, unconnected databases) may also affect whether, or to what extent, it meets its legal obligations under Penal Code Section 832.5 to report civilian complaints. Because agencies may silo the various sources of misconduct allegations (e.g., civilian complaints, use of force incidents, domestic violence complaints, complaints by peer officers or supervisors, etc.), failure to integrate this information among various databases may impair or entirely defeat an agency’s early intervention system that seeks to identify and remedy at-risk behavior as soon as possible.97 94 Ibid, p. 70. In August 2019, the Sacramento Police Department revised its complaint intake and investigation procedure in Internal Reference Manual 220.01, and in doing so appears to have eliminated the “inquiry” classification. 95 Los Angeles County Sheriff’s Department. (n.d.). 3-04/10.00, Department Service Reviews. In Manual of Policies and Procedures. Available at http://www.lasd.org/pdfjs/web/PublicComplaintPolicies.pdf. 96 Ibid, Sections 3-04/010.20 (Service Complaints) and 3-04/010.25 (Personnel Complaints). 97 See, e.g., USDOJ, Civil Rights Division. (2016). Investigation of the Baltimore City Police Department, p. 134. (Baltimore Police Department’s failure to use integrated systems to maintain information blunts the usefulness of this data; data is maintained in 232 separate databases, most of which cannot be linked to each other); California Department of Justice. (2019). Sacramento Police Department: Report & Recommendations, pp. 71-72 (recommending an early intervention program that collects and maintains, in a computerized database, various subsets of information, including civilian complaint data and disposition, as well as use of force allegations, disciplinary actions, awards and commendations, and training). 69 Without a uniform understanding of (1) what a complaint is under this section, and (2) how such complaints are handled internally, it is difficult to compare and contrast civilian complaints reported by agencies pursuant to Penal Code section 832.5. Because one of the goals of RIPA was to require agencies to provide more granular data regarding civilian complaints that allege racial or identity profiling, in order to better analyze these complaints, it is crucial that agencies use similar methods to define and track civilian complaints. Accessibility and Knowledge of an Agency’s Complaint Process Another factor that may explain the disparities in numbers of complaints between agencies and across years is different levels of community access to agency complaint processes. This has been a subject of discussion for the Board, as well as the subject of several grand jury reports in California.98 In particular, the Board’s review of the complaint processes of Wave 1 agencies demonstrates how agencies differ widely in how they publicize their complaint processes and the procedures by which they accept complaints. Barriers to accessing civilian complaint forms or processes could also explain the disparities in the number of reported complaints among agencies. In other words, one agency may report what seems like a disproportionately high number of civilian complaints, not because of inherent problems in how they interact with the community, but because their complaint system is widely publicized and individuals can easily submit complaints through the Internet, over the phone, or in their native language. By contrast, a different agency may have low numbers of reported complaints, not because they provide exceptional service, but because individuals cannot readily access a complaint form, or are required to mail or bring in complaints in person. Agencies should increase public access by developing an easily understandable and usable form, available in multiple languages and multiple formats that individuals may use to make complaints. A best practice would be to refrain from using any language in the form —such as requiring the complainant to sign under penalty of perjury — that could be reasonably construed as discouraging the filing of a complaint.99 98 See, e.g., 2012-2013 Santa Clara County Civil Grand Jury. (2013). Report: Law Enforcement Public Complaint Procedures. Available at http://www.scscourt.org/court_divisions/civil/cgj/2013/LawEnforcementPublicComplaintProcedures.pdf; 2015/2016 Marin County Civil Grand Jury. (2016). Law Enforcement Citizen Complaint Procedures: The Grand Jury has a few complaints. Available at https://www.marincounty.org/-/media/files/departments/gj/reports- responses/2015/law-enforcement-citizen-complaint-procedures.pdf?la=en; 2018 Los Angeles County Grand Jury Report. Available at http://www.grandjury.co.la.ca.us/pdf/2017- 2018%20los%20angeles%20county%20civil%20grand%20jury%20final%20report.pdf. 99 See, e.g., U.S. v. Police Department of Baltimore City, et. al. (2017) 1:17-cv-00099-JKB (mandating that the written notice of receipt sent to non-anonymous complainants should “not contain language that could be reasonably construed as discouraging participation in the investigation, such as a warning against providing false statements or a deadline by which the complainant must contact the investigator.”). 70 Possible Barriers to Reporting of Civilian Complaints • Lack of knowledge of complaint process: complaint processes may not be prominently featured on an agency’s website or literature. • Inadequate explanation of process: complainants may be confused or have misconceptions about the complaint process. • Language barriers: complaint processes may not be available in languages other than English. • Difficulty of complaint process: complaints may not be easily downloaded from a website or submitted online and may have to be filed in person. 100 • Inaccessibility of forms: forms may not be available on an agency’s website, in the complainant’s language, or physically available or easy to obtain at the agency’s public waiting area; if forms are not displayed in public waiting area, an individual may have to specifically state “I want to file a complaint” in order to initiate the process. Accessibility for People with Disabilities Another possible reason behind the disparities in the numbers of complaints among agencies is the varying degree of accessibility of the complaint process for people with disabilities. The Board seeks to ensure that individuals with disabilities have access to complaint forms. To that end, the Board reached out to Disability Rights California and other advocates to identify best practices to make complaint processes and forms more easily available and usable for individuals with disabilities.101 Given these discussions with stakeholders, the Board encourages law enforcement agencies to accept complaints filed in person, in writing, over the telephone, by Internet, by fax, anonymously, or on behalf of someone else, so that individuals with disabilities have multiple options to choose from based on what would be most assistive given their particular disability. 102 A phone-in option, for instance, 100 The USDOJ found, for example, that the Baltimore PD placed unnecessary conditions on the filing of complaints, including requiring many types of complaints to be signed, notarized, and filed in person at only a few locations. USDOJ, Civil Rights Division. (2016). Investigation of the Baltimore City Police Department, p. 140. 101 Accessibility to the complaint process is required by both state and federal law. USDOJ, Civil Rights Division. (n.d.). Information and Technical Assistance on the Americans with Disabilities Act: ADA enforcement in criminal justice settings. Available at https://www.ada.gov/criminaljustice/cj_enforcement.html. 102 See, e.g., Police Executive Research Forum. (2015). Critical Response Technical Assessment Review: Police Accountability – Findings and National Implications of an Assessment of the San Diego Police Department. Washington, DC: Office of Community Oriented Policing Services. Available at https://cops.usdoj.gov/RIC/Publications/cops-w0756-pub.pdf (“Consistent with accepted best practice, the 71 may be more accessible for individuals with low vision or blind. Agencies should also develop and use a language assistance plan and policy that includes protocols for interpretation (including Braille and American Sign Language).103 For example, the World Wide Web Consortium (W3C) has a well- established set of programming standards and resource materials to assist web page designers in making content accessible to persons with a variety of disabilities — such as blind persons using text- to-speech software.104 An agency can also increase accessibility by offering a trained staff member to assist with completing a complaint form. When creating form and policy documents for the public, agencies can use the following guidelines to make documents more accessible to individuals with disabilities in the following ways: 1. Documents should be easy to read. There are private vendors that have built-in accessibility check features that can identify solutions for accessibility errors in documents. There are also commercially available spelling and grammar checks that can score a document with a “Reading Ease Number” and a “Grade Level” for the readability of text. For the reading ease number, a score above 60 percent is recommended. For the reading level, a score between 7th and 9th grade reflects accessible text.105 2. The minimum font size should be 14 point. 3. Always use high contrast colors on text. Some people cannot see the text if the background color does not have enough contrast. 4. Text should be flush left. This makes it easier for people with disabilities to read the content.106 5. Numbered lists are more easily read than bullet points. 6. Correct formatting of the electronic document can make titles and headers, pictures, tables, footnotes, and endnotes accessible for assistive technology software/screen readers.107 SDPD has a multifaceted system for receiving complaints; community members in San Diego may file a complaint in person, by phone, by mail, or by e-mail”); U.S. v. Police Department of Baltimore City, et. al. (2017) 1:17-cv-00099-JKB (describing how Baltimore PD will ensure broad and easy access to its complaint system: “BPD will ensure individuals may make complaints in multiple ways, including in person or anonymously, by telephone, online, and through third parties”). See also recommendations in reports issued by the Los Angeles County Grand Jury, Santa Clara County Grand Jury, and Marin County Grand Jury. 103 See, e.g., U.S. v. Police Department of Baltimore City, et. al. (2017) 1:17-cv-00099-JKB (“Complaint forms will be made available, at minimum, in English and Spanish. Baltimore PD will comply with the law to make complaints accessible to people who speak other languages (including sign language). The fact that a complainant does not speak, read, or write English, or is deaf or hard of hearing will not be grounds to decline to accept or investigate a complaint.”). 104 See World Wide Web Consortium (W3C). (n.d.). Web Accessibility Initiative. Available at https://www.w3.org/standards/webdesign/accessibility. 105 Disability Rights California. Guide to Accessibility. AC 01; AC 08 – v.01. 106 Disability Rights California. Guide to Accessibility. AC 01; AC 09 – v.01. 107 Disability Rights California. Guide to Accessibility. AC 03; AC 06; AC 07; AC 09 – v.01. 72 Ensuring that individuals with disabilities have equal access to civilian complaint forms and processes not only fulfills agencies’ duties in complying with state and federal disability access laws, but will help agencies obtain valuable input from members of the disabled community. Deterrent Impact of Penal Code Section 148.6 Another factor that may impact the number of civilian complaints is the complainant’s desire for confidentiality, which may make the complainant reluctant to file a written or formal complaint. Compounding this reluctance is the deterrent impact of Penal Code section 148.6. Section 148.6 makes it a misdemeanor to file a knowingly false allegation of misconduct against a peace officer. (Pen. Code, § 148.6, subd. (a)(1).) In complying with this law, many agencies require the complainant to read and sign the following advisory, which is in all-capital letters and must be set forth in boldface type: YOU HAVE THE RIGHT TO MAKE A COMPLAINT AGAINST A POLICE OFFICER FOR ANY IMPROPER POLICE CONDUCT. CALIFORNIA LAW REQUIRES THIS AGENCY TO HAVE A PROCEDURE TO INVESTIGATE CIVILIANS’ COMPLAINTS. YOU HAVE A RIGHT TO A WRITTEN DESCRIPTION OF THIS PROCEDURE. THIS AGENCY MAY FIND AFTER INVESTIGATION THAT THERE IS NOT ENOUGH EVIDENCE TO WARRANT ACTION ON YOUR COMPLAINT; EVEN IF THAT IS THE CASE, YOU HAVE THE RIGHT TO MAKE THE COMPLAINT AND HAVE IT INVESTIGATED IF YOU BELIEVE AN OFFICER BEHAVED IMPROPERLY. CIVILIAN COMPLAINTS AND ANY REPORTS OR FINDINGS RELATING TO COMPLAINTS MUST BE RETAINED BY THIS AGENCY FOR AT LEAST FIVE YEARS. IT IS AGAINST THE LAW TO MAKE A COMPLAINT THAT YOU KNOW TO BE FALSE. IF YOU MAKE A COMPLAINT AGAINST AN OFFICER KNOWING THAT IT IS FALSE, YOU CAN BE PROSECUTED ON A MISDEMEANOR CHARGE. I have read and understood the above statement. Complainant _____ (Pen. Code, § 148.6, subd. (a)(2).) These two provisions collectively have the following effect: (1) knowingly false allegations are subject to misdemeanor criminal sanctions; (2) complainants cannot submit complaints anonymously; rather, they are required to provide their name (presumably in order to ensure they can later be prosecuted criminally if their allegation is knowingly false); and (3) complaints cannot be submitted orally but rather must be submitted in writing. 73 Although the Board understands the intent of Penal Code section 148.6 is to deter complainants from lodging false or frivolous allegations about peace officers, requiring complaints to be signed, in writing, and under penalty of criminal prosecution may create an unnecessary chilling effect upon the accurate reporting of civilian complaints, particularly those that allege racial or identity profiling.108 Many California law enforcement agencies have removed the warning from their civilian complaint forms and accept anonymous complaints.109 The California Attorney General’s Office has also determined that a law enforcement agency can investigate allegations of police misconduct, even if the complainant did not sign the admonition as required by Penal Code section 148.6. (Cal. Atty. Gen. Ops. No. 96-111 (1996).) Accordingly, in the 2019 RIPA Board report, the Board recommended that all agencies accept anonymous and verbal complaints: “Agencies should have an accessible, fair, and transparent complaint process. The process should be set forth in writing and made widely and permanently available within the agency and to the public. All complaints should be accepted, whether in person, in writing, over the telephone, anonymously, or on behalf of another individual.” As noted above, many agencies have already followed the Board’s recommendation. Given the strong public policy supporting the need to collect anonymous civilian complaints, and to resolve the existing conflict between state and federal law, the Board has asked the Legislature to 108 Moreover, imposing a criminal sanction for reporting false allegations about an officer is unnecessary and duplicative of an existing statute, Penal Code section 148, which makes it a misdemeanor and/or imposes a fine with respect to anyone “who willfully resists, delays, or obstructs any public officer, peace officer [. . .] in the discharge or attempt to discharge any duty of his or her office or employment.” (Pen. Code, § 148, subd. (a)(1)). In addition to the unwanted chilling effect and duplicative nature of the criminal sanctions currently in effect under Penal Code section 148.6 for filing a knowingly false allegation against a police officer, law enforcement agencies currently cannot determine with certainty whether they are required – or prohibited – from complying with the advisory requirements of Penal Code section 148.6. This is because the Ninth Circuit and California Supreme Court have come to opposite conclusions regarding whether the Penal Code section 148.6 is constitutional. Compare People v. Stanistreet (2002) 29 Cal.4th 497, 510 (Section 148.6 is a permissible regulation of prohibited speech, namely, false allegations against peace officers, which, on its face, does not violate the First Amendment to the United States Constitution) with Chaker v. Crogan (2005) 428 F.3d 1215, 1222, cert. denied, 547 U.S. 1128 (2006) (Penal Code §148.6’s criminal sanction violated the First Amendment of the United States Constitution because it regulated content-based speech on the basis of that speech’s content). 109 See, e.g., San Francisco Police Department. (2018). Department Bulletin 18-161. Available at https://www.sanfranciscopolice.org/sites/default/files/2019-05/A%2018- 161%20False%20Allegations%20of%20Misconduct%20against%20Peace%20Officers%20Penal%20Code%20Secti on%20148.6%20%28Re-issue%20DB%2010-134%29.pdf (noting that “In light of a standing conflict between California and Federal law, members shall not make arrests pursuant to Penal Code Section 148.6 unless they have first consulted the District Attorney’s Office for a filing decision and obtained an arrest warrant … [T]he Ninth Circuit’s conflicting decision leaves members vulnerable to federal lawsuits.”); Santa Clara County Civil Grand Jury. (2013). 2012-2013 Santa Clara County Civil Grand Jury Report: Law Enforcement Public Complaint Procedures [PDF file]. Available at http://www.scscourt.org/court_divisions/civil/cgj/2013/LawEnforcementPublicComplaintProcedures.pdf (recommending the removal of Section 148.6 language, as well as any references to Civil Code section 47.5). 74 eliminate the criminal sanctions by deleting or amending the language in Penal Code section 148.6, subdivision (a), and to amend the statute’s requirement that a complaint must be signed and in writing. 2018 Civilian Complaints for Wave 2 and 3 Agencies The Board examined the civilian complaint data for the Wave 2 and Wave 3 agencies. The number of complaints reported by these agencies showed notable disparities, for the same reasons explained above. 2018 Civilian Complaints for Wave 2 Agencies Table 6 displays civilian complaints received in 2018 by California's medium-large agencies (Wave 2 agencies), which have between 667 and 999 sworn personnel. These agencies began collecting stop data on January 1, 2019. Table 6: Wave 2 Agency Complaints and Sworn Personnel Agency Total Profiling Sworn Personnel Complaints Allegations Reported Reported Orange County Sheriff’s 98 8 1,880 Department (8%) Sacramento County 303 8 1,302 Sheriff’s Office (3%) San Jose Police 217 36 1,113 Department (17%) Fresno Police 171 8 811 Department (5%) Long Beach Police 210 8 824 Department (4%) Oakland Police 1,396 58 731 Department (4%) 75 Agency Total Profiling Sworn Personnel Complaints Allegations Reported Reported Sacramento Police 4 0 651 Department Note: The percentages in the Profiling Allegations Reported column display the proportion of the Total Complaints Reported column that alleged racial or identity profiling for each agency. 2018 Civilian Complaints for Wave 3 Agencies Agencies with 334 to 666 non-custodial sworn personnel make up Wave 3. This wave of reporting agencies begins stop data collection on January 1, 2021. Complaint and sworn personnel information for these agencies is found in Table 7. Table 7: Wave Three Agency Complaints and Sworn Personnel Agency Total Complaints Profiling Sworn Personnel reported Allegations Reported Santa Clara County 30 2 1,279 Sheriff’s Office (7%) Alameda County Sheriff’s 62 1 939 Office (2%) San Francisco County 66 1 860 Sheriff Department (2%) Kern County Sheriff’s 142 3 806 Office (2%) Ventura County Sheriff’s 67 12 760 Office (18%) Stockton Police 11 4 469 Department (36%) 76 Santa Barbara County 27 3 454 Sheriff’s Office (11%) Anaheim Police 71 4 419 Department (6%) Fresno County Sheriff’s 38 11 430 Office (29%) Bakersfield Police 49 0 398 Department Riverside Police 58 2 370 Department (3%) Los Angeles World Airport 31 0 --- Police Note: The percentages in the Profiling Allegations Reported column display the proportion of the Total Complaints Reported column that alleged racial or identity profiling for each agency. The Los Angeles World Airport Police did not report personnel counts to the Department for 2018, so this information is missing from the table. The above tables are intended to provide a high-level glimpse at information available for the larger agencies (i.e., those who employ 333 or more non-custodial sworn personnel; Waves 1 to 3, inclusive), which will all collect stop data by 2021. For a complete look at the data, including the dataset containing agencies of all sizes and an extended catalogue of data elements beyond what is available in the tables above, please visit https://openjustice.doj.ca.gov/data. 77 Overview of Complaints Collected between 1981-2018 Board members were also interested in broader trends in the civilian complaints against all reporting law enforcement agencies over a longer time period. As mentioned above, law enforcement agencies employing peace officers have been submitting complaint data to the Department since 1981; giving us the ability to examine trends in this data over the past 37 years. Below, Figure 15 displays the number of civilian complaints reported by these agencies from 1981 to 2018.110 The total number of civilian complaints reported trended upwards from 1981 until 2007; agencies experienced a general decline until 2015, after which began another period of increased complaint totals. Across all agencies and all years since 1981, the average total yearly number of civilian complaints is 17,751 (Standard Deviation=3,850). The highest number of civilian complaints (24,358) were reported in the year 2007, while the lowest number of civilian complaints (8,686) were reported in 1981, the first year of data collection. In 2018, the most recent year available, 702 agencies reported a total of 16,525 complaints. Reviewing the totals from the 10 most recent years of data (2009 – 2018), 2018 ranks the 4th lowest. Figure 15. Statewide Complaints Reported by Year (1981-2018) 30000 25000 20000 15000 10000 5000 0 110 Figure 15 is derived from the Summary dataset in the Civilian’ Complaints Against Peace Officers section of the OpenJustice webpage. California Department of Justice. (2019). Civilian Complaints Against Peace Officers: Summary [CSV file]. Available at https://openjustice.doj.ca.gov/data. 78 detropeR stnialpmoC 1891 2891 3891 4891 5891 6891 7891 8891 9891 0991 1991 2991 3991 4991 5991 6991 7991 8991 9991 0002 1002 2002 3002 4002 5002 6002 7002 8002 9002 0102 1102 2102 3102 4102 5102 6102 7102 8102 Civilian Complaints Reported 1981-2018 Year To contextualize the total annual number of complaints received over a 37-year period, it is helpful to take into account the changing population of both residents and law enforcement over time. Figure 16 below displays the number of civilian complaints reported per 10,000 California residents (per capita) from 1981 to 2018. The figure also displays the number of civilian complaints reported per 10,000 sworn personnel employed by law enforcement agencies in the state from 1991 to 2018. The California population grew from an estimated 24,039,000 residents in 1981 to an estimated 39,740,508 residents in 2018, a 65.3 percent increase.111 The number of sworn personnel employed by California law enforcement agencies grew 29.9 percent between 1991 (60,901) and 2018 (79,113).112 Considering the annual complaint totals in the context of changing populations can paint a different picture. By examining the raw numbers, 2018 experienced the 15th lowest total number of civilian complaints out of all 38 data collection years (see Figure 15), whereas by examining per capita complaint rates, 2018 experienced the 5th lowest per capita complaint rate. Examining complaints in the context of the number of sworn law enforcement personnel, 2018 had the fourth lowest complaint rate in all years since 1991. Figure 16. Complaints Reported per 10,000 Residents and Sworn Personnel by Year (1981-2018) 8.0 4000 7.0 3500 6.0 3000 5.0 2500 2018 4.0 2000 3.0 1500 2.0 1000 1.0 500 0.0 0 1 3 5 7 9 1 3 5 7 9 1 3 5 7 9 1 3 5 7 8 8 8 8 8 9 9 9 9 9 0 0 0 0 0 1 1 1 1 9 9 9 9 9 9 9 9 9 9 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 111 The statewide population estimates used in the per capita complaint rate displayed in Figure 16 are available from the California Department of Finance Demographic Research Unit’s Estimates webpage: http://www.dof.ca.gov/Forecasting/Demographics/Estimates/. 112 The Criminal Justice Statistics Center (CJSC) at the Department of Justice collects information on the number of sworn law enforcement personnel employed by law enforcement agencies in California. The CJSC collects these data through a one-day survey taken on October 31st of each reporting year. 1991 is the earliest year law enforcement personnel data were collected in this way. 79 stnediseR 000,01 rep detropeR stnialpmoC lennosreP nrowS 000,01 rep detropeR stnialpmoC Complaints and Sworn Officers per Capita Year Complaints Reported per 10,000 Residents Complaints Reported per 10,000 Sworn Personnel Information to Be Included in Future Civilian Complaint Reporting In last year’s report, the Board recommended several changes to the Department’s reporting of civilian complaints.113 The Department has adopted several of these recommendations for future reporting.114 The recommended changes are the following: (1) Agencies must include specific counts of dispositions of complaints that were initially reported during the statistical year (i.e., complaints that were reported and resolved in the same calendar year will be counted separately from complaints that have not been reported and resolved in the same calendar year). Likewise, complaints that reached dispositions in a different year from when they were originally reported will have separate counts so that they can be distinguished from the more recent complaints. (2) The Department will report complaints made in detention facilities separately from other complaints, in order to analyze complaints stemming from custodial and non-custodial settings. (3) Non-criminal, misdemeanor, and felony categories will be further disaggregated by offense level for disposition and profiling category totals. 113 Racial and Identity Profiling Advisory Board. (2019). Racial and Identity Profiling Advisory Board Annual Report 2019 [PDF file], p. 37. Available at https://oag.ca.gov/sites/all/files/agweb/pdfs/ripa/ripa-board-report- 2019.pdf. 114 Although the Department initially anticipated implementing these changes for this year’s reporting cycle, these changes will require overhauling the Department’s database and collection systems for civilian complaints. As a result, the data collection will begin in 2020 and the data will be reported to the Department in 2021. 80 Review of Wave 1 Agency Complaint Forms The Board conducted a thorough review of the complaint forms for all Wave 1 agencies – Los Angeles Police Department, California Highway Patrol, Los Angeles County Sheriff’s Department, San Francisco Police Department, San Diego Police Department, Riverside County Sheriff’s Department, San Diego County Sheriff’s Department, and San Bernardino County Sheriff’s Department. These forms were submitted to the Board in the survey included in the 2018 annual report or found on the agencies’ websites. This review identified some pros and cons to the various complaint forms: Pros Cons • Some forms include detailed • Several agencies did not have the form information on the agency’s complaint easily accessible on their websites. policies and procedures. • One agency does not have any form • Some forms were integrated with the (though it has information on its forms/processes of their civilian website regarding to whom to submit a review board. complaint). • Information about complaints for each • Not many agencies make the agency is accessible by a simple information readily available in Google search, though the form was multiple languages. not always the first search result. • Some forms or corresponding • Some forms ask specifically about instructions do not make the racial or identity profiling. submission of the complaint form and • One form specifically asked if anyone follow-up procedures easily in the agency attempted to discourage understandable. the complainant. • Not all agencies specifically allow for • One form included pre-paid postage. online or email complaint submission. • Some forms do not include a narrative field for a description of the incident. Best Practice Recommendations Our review uncovered inconsistencies in agencies’ civilian complaint processes, particularly regarding the accessibility of complaint forms. The Board acknowledges that there is no funding associated with the mandate that agencies develop civilian complaint processes. To reduce some barriers at minimal cost, the Board encourages agencies to partner with local academics or community organizations to assist, for example, with the translation of forms into additional languages. 81 In its 2019 report, the Board made recommendations for best practices for civilian complaint procedures and policies. In this report, the Board makes recommendations regarding the civilian complaint forms. After reviewing literature regarding best practices for civilian complaint procedures and forms and conducting an initial review of the Wave 1 agency civilian complaint review forms, the Board recommends that agencies consider the following in assessing and, if appropriate, revising their complaint procedures and forms: Introductory or Background Information • The agency’s complaint form should include an explanation of the policy to provide the complainant with clear direction on complaint procedures. • The agency’s policies, applicable forms, and training materials should communicate a clear, consistent definition of the term “civilian complaint.” • Complaint forms should include specific instructions for how to fill out and submit the complaint, as well as the contact information of specific department personnel who can assist in completing the form. • The form should include pertinent information from the agency’s complaint policy and procedures, such as: o A link to the agency’s complaint policy. o A statement on the agency’s commitment to the acceptance and prompt, fair, and thorough investigation of all complaints regardless of submission method or source. o A statement that retaliation for making a complaint or cooperating in a complaint investigation is contrary to agency policy and may also be unlawful. The statement may encourage individuals to report any retaliation they face. o A statement on the protection of personal information except as necessary to resolve the complaint. This should include a notice that the information is subject to the State’s public disclosure laws. o A definition of racial or identity profiling consistent with RIPA. o Information about the investigation process, including the potential finding dispositions and the timeline. o Information on whom to contact regarding updates on the investigation of the complaint. 82 General Complaint Information • The form should capture: o If the complaint is being submitted anonymously, by a third party, or on behalf of a minor; o If a translator has been requested; o How the complaint was submitted (e.g., online, mail, in person). • The form should include the name and contact information for agency personnel who filed or collected the complaint. • The form should be accessible for people with disabilities. Complainant Information • The form should ask for the following relevant information about the complainant (if the complainant so chooses): o Name o Age o Gender o Race or Ethnicity o Sexual Orientation o Primary Language o Address o Home, work, mobile phone numbers. o E-mail Address Incident Information • The form should capture relevant information about the incident, including: o The location of the incident o Date of incident o Time of incident o If the incident was the result of a traffic or pedestrian stop o If the incident resulted in bodily injury § Including a narrative description field 83 § If photos or videos of the injury were included with the complaint o If the complainant was present at the incident o If the incident was based in whole or in part on any factors such as: § Actual or perceived race, color, ethnicity, national origin, age, religion, gender identity or expression, sexual orientation, or mental or physical disability115 § Inappropriate use of force § Improper detention, search, or arrest § Substandard officer performance o Witness information, to the extent known o The name or a description of the officer(s)/employee(s) involved (potentially including Badge or ID number) o If the complaint or a related complaint has been previously submitted o A large narrative field for description of the alleged misconduct. Processing of Complaints The agency’s civilian complaint procedures should clearly explain how various types of complaints will be received, logged, and reviewed. The procedure should require that all complaints – including those that may be reviewed by a civilian review board or different branch within the department (for example, Internal Affairs) – be logged into a central civilian complaint repository to facilitate systematic analysis of these complaints. The agency’s complaint procedure should also include a time frame within which civilian complaints are to be investigated and a resolution reached. The Board hopes that agencies will work to implement the Board’s best practice recommendations for handling civilian complaints. These recommendations will help ensure that complaints submitted to the Department accurately reflect the number of complaints of racial and identity profiling. As with all of its recommendations, the Board notes that these recommendations are merely a starting point and not an exhaustive list of best practice recommendations for civilian complaint procedures. 115 Agencies may consider including language similar to the following: If you believe that the misconduct is based in whole or in part on your race, color, national origin, sex, gender identity, religion, or disability, please identify the basis and explain what led you to believe that you were treated differently from others. 84 Wave 1 Agency Civilian Complaint Form Review The Board requested current civilian complaint forms from all Wave 1 agencies. The California Highway Patrol, San Bernardino County Sheriff, San Diego County Sheriff, Riverside County Sheriff and San Diego Police Department provided updated civilian complaint forms. The civilian complaint forms for the Los Angeles Police Department, Los Angeles Sheriff, and San Francisco Police Department were obtained online. The matrix below summarizes the Board’s review of the most recent civilian complaint forms, based on the best practices outlined in the 2019 RIPA Board Report. Following the matrix is a more detailed review of each agency’s civilian complaint form. The recommendations represent an accumulation of best practices identified by the USDOJ and other relevant empirical research conducted by well-regarded organizations, including the Police Executive Research Forum (PERF) and the International Association of Chiefs of Police (IACP). To ensure accuracy, the Department shared this review with the Wave 1 law enforcement agencies before including it in the report. Many of the categories assessed below focus on the first step of the complaint process, namely making a complaint. To that end, the Board evaluated basic access to filing a complaint by assessing whether a third party can submit the form, whether it is available online, and whether it is available in multiple languages. Additionally, in reviewing the public’s access to the complaint process, the Board examined whether the complaint can be submitted online and by what other methods complaints are accepted. The Board also reviewed whether the complaint form might deter members of the public from reporting a complaint by referencing language from Penal Code Section 148.6. Furthermore, the Board evaluated whether members of the public are allowed to give full information about the incident and whether they are informed about how they can follow up about their complaint by assessing whether there is a narrative section on the form and whether the civilian complaint process information is included on or attached to the form. 85 Form Accessible Can Submit Multiple Methods Available in Multiple Wave 1 Agency Online? Online? of Submission? Languages?116 CHP ü ü ü ü LAPD ü ü ü ü Los Angeles ü û ü ü Sheriff San Diego PD ü û ü ü San Francisco PD ü ü ü ü San Diego Sheriff ü û ü ü Riverside Sheriff û û ü û San Bernardino ü û ü ü Sheriff 116 Federal and state law require federally and state assisted law enforcement agencies to provide meaningful access to Limited English Proficient (LEP) individuals. Under federal law, to determine the extent of its obligation to provide services to the LEP population, the Federal Coordination and Compliance Section recommends that law enforcement agencies engage in a four-factor analysis. (USDOJ, Federal Coordination and Compliance Section. (2002). Planning Tool: Considerations for Creation of a Language Assistance Policy and Implementation Plan for Addressing Limited English Proficiency in a Law Enforcement Agency). California state law also requires local agencies that receive state funding to provide language access services to LEP populations. (Gov. Code, § 11135, subd. (a); Gov. Code, § 7290). LEAs may ask local community-based organizations to help translate complaint forms or create a database of qualified interpreters for speakers of any language, including sign language. 86 Complaint Third Party Includes Narrative Does Not Include Process Wave 1 Agency Complaints Field for Description Language from PC Information Allowed? of Complaint? § 148.6?117 Attached to Form? CHP ü ü ü û LAPD ü ü ü û Los Angeles ü ü ü ü Sheriff San Diego PD ü ü ü ü San Francisco PD ü ü ü û San Diego ü ü û ü Sheriff Riverside Sheriff ü ü û ü San Bernardino ? ü û û Sheriff 117 It is not a requirement that the Penal Code be included. In fact, there is a conflict between federal and state law on whether anonymous complaints should be accepted. One federal court has found that § 148.6(b) violates the First Amendment. (Chaker v. Crogan (9th Cir. 2005) 428 F.3d 1215). However, the California Supreme Court in 2002 upheld the constitutionality of § 148.6. (People v. Stanistreet (2002) 29 Cal.4th 497). Nevertheless, the Board recommended that all agencies accept anonymous and verbal complaints. Thus, a checkmark indicates that the Department does not mention PC 148.6 or its language in their complaint form. The RIPA Board believes the California legislature should address this conflict soon, since the requirements set out by the Penal Code can have a chilling effect on the submission of civilian complaints. 87 California Highway Patrol The California Highway Patrol permits members of the public to submit civilian complaints (1) online, (2) by mail, (3) by phone, and (4) in person. However, instructions are not provided online about how to submit a complaint by phone or in-person. The online submission is in English, but the printed forms are available in English and Spanish. The second page of the form provides the phone number and address of the Office of Internal Affairs should assistance be needed. Clear instructions are not provided about how to submit the printed forms. The complaint investigation process is explained online where Penal Code § 148.6 is referenced, and it is stipulated that all complainants will be required to read and sign a Civilian Complaint Information form. CHP responds to third party complainants by acknowledging receipt of their concerns and informing them that the allegedly aggrieved party will be contacted directly. Policy HPM 10.4 Chapter directs agency command to “contact the complainant [allegedly aggrieved party] directly to ascertain their intentions, normally with a requested turnaround period of 30 days.” The printed civilian complaint form was last updated December 2015. Los Angeles Police Department The Los Angeles Police Department allows members of the public to file a civilian complaint: (1) in person at any police facility, (2) to the Internal Affairs Group, (3) to the Police Commission, or (4) to the Office of the Inspector General. The Complaint of Employee Misconduct form is available at any Los Angeles community police station, the Police Commission, the Office of the Inspector General or any City Council field office. The form is available in English, Spanish, Chinese, Cantonese, Korean, Japanese, Tagalog, and Vietnamese. The Personnel Complaint Information pamphlet is not attached but is displayed next to and made available with the complaint form. A 24-hour toll-free hotline, where complaints can be made in all languages, is provided on the LAPD website and in the complaint information pamphlet. The pamphlet additionally provides a Text Telephone (TTY) number to file a complaint or request the complaint form. The complaint information pamphlet lists mailing addresses for the Internal Affairs Group, the Office of the Chief of Police, and the Board of Police Commissioners, in addition to a fax number, for submitting written complaints. The online complaint form is available in English. The complaint investigation process is explained on their website. Anonymous and third- party complaints are accepted and will be investigated to the extent that sufficient information is provided. The complaint form asks if the specific complaint or any related complaint was previously reported. Los Angeles County Sheriff The Los Angeles County Sheriff’s Department allows members of the public to submit civilian complaints: 1) in writing to any Sheriff’s station, jail, or facility, 2) in person to the Watch Commander or person in charge, 3) by phone, or 4) by mail. The civilian complaint form is available on the agency’s website in English and Spanish and is two pages long, with the first page spelling out the complaint process. The form explicitly asks if any member of the agency attempted to discourage the complainant. The Los Angeles Sheriff’s Department has removed any reference to Penal Code § 148.6 from the public complaint process. The LASD document “Personnel Complaints” specifies that the agency will accept and review any comment from any member of the public concerning agency service 88 or individual performance. LASD categorizes public complaints as either personnel complaints or service complaints. San Diego Police Department The San Diego Police Department receives citizen complaints: (1) in person at stations, (2) by phone or in writing to Chief of Police, (3) by phone to SDPD Communications Division, (4) by phone or writing to Internal Affairs Unit, (5) to the Office of the Mayor, and (6) in person, by phone, online, or in writing to the Community Review Board on Police Practices (CRB). The Department’s complaint form is not available online and is currently being translated to Spanish. Instructions on the form include a link to the complaint form page of the CRB website. The form was last updated on July 1, 2019. The CRB’s complaint forms are available in English and Spanish on its website. Information on the complaint investigation process is provided online and on the civilian complaint form itself. Third-party submissions are accepted. The form asks if any video or photos are included with the complaint and also inquires about the gender and race of the San Diego PD personnel involved. San Francisco Police Department Unique among the Wave 1 agencies, civilian complaints regarding the San Francisco Police Department are handled by the Department of Police Accountability (DPA), an independent department within the City and County of San Francisco. DPA has exclusive control of their internal processes related to complaint form content and format. Civilian complaint forms and investigation information are available on the DPA’s website, which is linked to the SFPD’s website. Civilian complaints can be submitted: (1) in person at stations, (2) by phone to SFPD or DPA, (3) online at DPA website, or (4) by mail to DPA. SFPD accepts all complaints of official misconduct, including anonymous and third-party complaints. The online submission form is available in English, Spanish, Chinese, and Tagalog. The mail-in form includes prepaid postage and, in addition to the other four languages noted, has also been translated into Russian and Vietnamese. The online submission form solicits more detailed information than the printed form, such as: noting special contact information if the complainant is experiencing homelessness or is in transition; whether an injury was sustained and whether photos were taken of the injuries; whether there is video or audio recording of the incident; whether medical attention was received; and whether a complaint has previously been filed. San Diego County Sheriff The San Diego County Sheriff’s Department allows members of the public to submit civilian complaints: (1) in person at stations, (2) by phone or mail to the Internal Affairs Unit, or (3) by contacting the Citizens’ Law Enforcement Review Board (CLERB) by email or mail. Any person may file a complaint. The Sheriff’s complaint form is not available online, but the agency’s website links to a complaint form on CLERB’s website. The complaint form includes a specific section dedicated to a complaint regarding racial or identity profiling and includes a checkbox to indicate racial and identity profiling. Last updated in December 2016, the form is available in English with instructions in both English and Spanish. The Sheriff’s Department additionally makes print complaint forms available in English and Spanish. 89 Riverside County Sheriff The Riverside County Sheriff’s Department accepts civilian complaints: (1) in person at any station or at the Sheriff’s Professional Standards Bureau, (2) by phone, or (3) in writing. Any person may file a complaint. The complaint investigation process is explained on the form itself and online. The form also warns against “filing a false complaint,” citing Civil Code Section 47.5, and references Penal Code Section 148.6. Additionally, the form specifically asks complainants to select which racial or identity group they perceive as the basis for the alleged racial or identity profiling. The form was last updated May 2017 and is currently being translated to Spanish. San Bernardino County Sheriff The San Bernardino County Sheriff’s Department accepts civilian complaints (1) in person at stations or Internal Affairs Headquarters or (2) by mail to Internal Affairs. The complaint investigation process is explained online. Last updated June 2018, the form is available in English and Spanish and includes a section on racial or identity profiling citing PC 13519.4(e). 90 POST Training Related to Racial and Identity Profiling As a part of RIPA’s requirements, the Board is charged with reviewing law enforcement training related to racial and identity profiling and analyzing the training developed by the Commission on Peace Officer Standards and Training (POST). POST is a state agency established to provide minimum testing, hiring, and training standards for peace officers in California.118 While participation in POST is voluntary, most California law enforcement agencies participate in the POST program and are therefore eligible to receive the services POST offers. Across California, there are 39 POST-certified basic law enforcement training academies that present POST’s Regular Basic Course training to officers. California Penal Code section 13519.4 charges POST with developing and disseminating guidelines and training on the racial and cultural differences among California residents. The law requires that any course of instruction should teach an understanding and respect for racial, identity, and cultural differences and instruct peace officers on how to conduct themselves in this type of environment. In its 2019 report, the Board compiled a list of recommendations for POST’s “expanded training/refresher [racial and identity profiling] course” under Penal Code section 13519.119 As discussed below, POST has begun implementing these recommendations. I. OVERVIEW OF THE BOARD’S COLLABORATION WITH POST REGARDING TRAINING The Board and POST have continued to work together to fulfill the important training requirements set forth in Penal Code section 13519.4. After receiving recommendations from the Board, POST created a new in-person Bias-Free Policing training to replace a prior version. The new training is currently in production; it is expected to be completed in Fall 2019 and effective in Spring 2020. POST also updated its existing Principled Policing training to include a racial profiling component and plans to integrate this training into management courses in the future. Classroom-Based Course POST currently offers an existing classroom course on Procedural Justice for in-service personnel and is developing a self-paced refresher course. As a companion to these courses, POST is designing a student-centered course on Principled Policing for entry-level officers in the basic academy. For its student-centered course, POST evaluated the in-service course (which was developed with input from the RIPA Board) by presenting pilot courses at three academies, conducting assessments with instructors and students, and discussing the proposed new Principled Policing course with administrative staff. After compiling and analyzing this data, POST convened a workshop in June 2019 attended by subject matter experts from law enforcement, community members, educators, instructional designers, and POST representatives. Subsequent workshops were held in August and November 2019. The benchmarks for designing this new course are set forth below. 118 Pen. Code, §§ 13500-13553. 119 Pen. Code, § 13519.4, subds. (a)-(h). 91 • Completed: The existing Training and Testing Specifications (TTS) for Learning Domain 3 of the Basic Course were modified to include Principled Policing/Procedural Justice. This course was renamed Principled Policing in the Community. Key learning objectives of this course address the four tenets of procedural justice: implicit bias, explicit bias, cultural competency, impact of historical events on community and officer perspectives, and cynicism. POST approved these TTS modifications in October 2019, and they are set to be effective April 1, 2020, pending completion of the Office of Administrative Law review process. Eight (8) additional hours of facilitated instruction will be added to the Basic Course. • Completed: Principled Policing content was added to the existing Learning Domain 3 Student Workbook to support the Training and Testing Specifications and course of instruction. • Completed Draft: Design and development of a draft of an eight (8) hour course of instruction entitled Principled Policing. The course is designed to invoke critical thinking, student interaction, and reinforce the crucial value of principled policing and procedural justice on both the community and the policing profession. The course also meets the requirements set forth in SB 230 (the new California law regarding training and policies for use of deadly force)120 for a basic course of instruction to include implicit bias, explicit bias, and cultural competency. • Completed Draft: A 24-hour Train-the-Trainer course for instructors to enhance proficiency of instructors to effectively deliver and facilitate student learning for the Principled Policing training. Included with the training will be the opportunity for instructors to receive additional coaching from training experts to ensure highly competent facilitated delivery of the material. The tentative schedule moving forward anticipates delivering pilots of the Train-the-Trainer (T4T) course in various locations throughout the State beginning in January 2020. The T4T and the inclusive eight (8) hours of instruction will be assessed and evaluated. Members of the RIPA Board will be invited to participate in the assessments to provide valued input. Modifications, if necessary, will be ongoing to ensure curriculum relevancy and consistency with the learning objectives of the in-service course and the developing self-paced course described above, as well as the impact of the training on entry-level peace officers and community members. Self-Paced Refresher Course POST is in the process of creating a self-paced refresher course (in consultation with SMEs) to meet the mandate for refresher training every five years set forth in Penal Code section 13519.4; this process requires analysis, design, development, and review phases before the course is released to the field. The refresher course is for both line officers and supervisors and will be accessed via the POST Learning Portal. In the analysis phase of the self-paced course, POST had one-on one interviews with RIPA Board Members Ben McBride, Warren Stanley, Sandra Brown, Marianna Marroquin, and David Robinson, as well as the late Judge Alice Lytle. POST is now in the design phase of this self-paced course. POST has worked with SMEs from the Museum of Tolerance and their trained instructors to establish sound learning objectives in line with 120 SB 230 requires POST to “implement a course or courses of instruction for the regular and periodic training of law enforcement officers in the use of force.” 92 the mandate established in Penal Code section 13519.4. POST has also begun creating prototypes of learning and evaluation activities for the course and testing them with both SMEs and end users (law enforcement officers subject to the training mandate). This type of input, combined with other sources of feedback, helps the POST determine early on if activities are instructionally effective. Some prototypes may be discarded while others will be built out for the final version of the course. Next, POST will be reaching out to community leaders recommended by Board members, and others who assisted in the creation of POST’s training video, to conduct content creation, review, and feedback sessions on the learning and evaluation activities. This will be an ongoing activity, as POST develops the content of the course and vets the learning and evaluation, along with e-learning instructional designers and SMEs. Once the course is placed into its initial draft form, POST will then invite RIPA Board members, including those on the POST subcommittee, to review and comment on the course. Early in 2020, POST will begin development on a “supervisor module” companion to the course. This “module” will be designed to provide tools and best practices, and assist supervisors and leadership in supporting their officers outside of the training course. The course is on track for release in Summer 2020. The supervisor module is expected to be released within six months after the release of the main course. POST’s Racial Bias and Profiling Video POST is also in post-production of a training video entitled Racial Bias and Profiling. This video will be eligible for Continuing Professional Training (CPT) credit and is another method of completing the Racial Profiling refresher requirements identified in Penal Code section 13579.4. The training video will be available to California peace officers via the POST Learning Portal, where officers can watch the video and then add the record of the completed training to their individual POST training profiles. The training video was developed through collaboration with Greg Anderson from the Fresno County DA’s Office, Basim Elkarra of the Council on American Islamic Relations (CAIR), Mark Katrikh from the Museum of Tolerance, Scott Meadors from the Stockton Police Department, Chief Gary Montecuollo of the Glendale Community College Police Department, LGBTQ advocate Michelle Rosenblum, and Judge Lytle.121 The SMEs first met in October 2018 to develop the program’s objectives and draft scenario scripts. During the second meeting in December 2018, the SMEs reviewed the scripts and monitored video production of the scenarios to ensure the appropriate objectives were being brought forth. The program’s educational objectives included officers’ understanding that: community perspectives and law enforcement’s ability to provide quality services are affected by historical events; the uniform “has a voice” even though today’s officer may not have been involved in past incidents; every contact matters; implicit bias is revealed through thoughts or feelings that one is unaware of and that affect one’s decision making; only non-biased and non-prejudicial approaches to their duties allow officers to enforce the law objectively and equitably; the violation or act – not the person committing it – is the basis for law enforcement action; and treating all people with respect and dignity – regardless of their cultural or social associations – enhances law enforcement effectiveness and community 121 POST intends to dedicate this program to the memory of Judge Lytle in light of her passion and dedication to this project. 93 perceptions. These significant points, and many others, are reinforced via the student and facilitator guides that are downloaded with the video when individuals complete or present the training. In February 2019, the SMEs met again to review the rough scenarios and monitor the filming of a “squad-room-styled briefing,” where a facilitator reviews each scenario with officers and leads discussions to ensure the course objectives are met. Then SMEs were interviewed individually so their perspectives and comments could be included in the final program. POST expects the video to be completed and released by December 2019. California Department of Justice POST Certified Course As part of its work with respect to the collection of the RIPA stop data, the Department is currently developing a POST-certified course. The course will be developed and administered by the Department’s Client Services Program in collaboration with the Civil Rights Enforcement Section. The overriding objective of the course will be to provide in-depth training to law enforcement to help them better understand the RIPA statute and its implementing regulations with the additional goal of ensuring uniform data reporting across all agencies. Although still in the early stages of development, it is anticipated that the course will be three to four hours in length and will be administered four to six times a year in various locations throughout California. In addition to the in-person learning sessions, the Department hopes to distribute the content of the course via multiple learning approaches including: classroom discussions, presentations, videos, and handouts. Specifically, the RIPA training course is meant to provide essential knowledge of the history, mandates, statutory and regulatory reporting requirements, explain uses for the data including supervisory review and oversight, and ensure uniform reporting. It is anticipated that this course will be implemented in mid-2020. As this training is still in the development phase, the Department welcomes suggestions from the Board, the community, and law enforcement agencies alike. II. VISION FOR FUTURE REPORTS The Board will continue to analyze POST’s trainings on bias-free policing and racial and identity profiling to ensure that its trainings incorporate the most up-to-date evidence-based best practices. In addition to training, the Board hopes to explore best practices in hiring and recruitment, performance assessment, and promotion practices in the coming years. 94 Relevant Legislation Enacted in 2019 Each year, the RIPA Report also highlights any relevant legislation from the previous year. New legislation can impact the Board’s work with law enforcement agencies and POST since it may change law enforcement agency’s policies and procedures, both with respect to bias-free policing and civilian complaints, as well as influence the training conducted by POST and reviewed by the Board. On August 19, 2019, California Governor Gavin Newsom signed Assembly Bill 392, which makes a significant change to when law enforcement can use deadly force. Previously, an officer could use “objectively reasonable” force to make an arrest, prevent escape, or overcome resistance. Now, under AB 392, an officer’s use of deadly force is limited to those circumstances when the officer reasonably believes that, based on the totality of the circumstances, deadly force is “necessary” to: a) Defend against an imminent threat of death or serious bodily injury to the officer or another person; or b) Apprehend a fleeing person for any felony that threatened or resulted in death or serious bodily injury if the officer reasonably believes that the person will cause death or serious bodily injury to another unless immediately apprehended. The law establishes the following definitions: 1. “Deadly force” means any use of force that “creates a substantial risk of causing death or serious bodily injury.” 2. A threat of death or serious bodily injury is “imminent” when a reasonable officer would believe “that a person has the present ability, opportunity, and apparent intent to immediately cause death or serious bodily injury.” 3. “Totality of the circumstances” means “all facts known to the peace officer at the time, including the conduct of the officer and the subject leading up to the use of deadly force.”122 AB 392 also makes three other important changes to current law. First, the new law emphasizes de- escalation and alternatives to the use of deadly force. Second, AB 392 provides that the conduct of the officer and subject leading up to the use of deadly force must be included in the evaluation of the officer’s decision to use deadly force. Third, AB 392 also prohibits the use of deadly force against a person based only on the danger that the person poses to themselves. Finally, although AB 392 makes significant changes to the standard for the use of deadly force, the new law does not significantly impact the standard for the use of non-deadly force. The law will take effect on January 1, 2020. California is the first state to uniformly use this standard for peace officers’ use of deadly force through legislation, though individual California police departments and those in other states have elements of the law in their use of force policies. 122 Cal. Penal Code § 835(e). 95 Conclusion Going forward, the Board will continue to study changes to best practices that may inform law enforcement policies and practices that intersect with racial and identity profiling. We will continue our focus on evaluating the stop data for any disparities that may impact certain racial and ethnic groups, but hope to expand our review in the coming years to evaluate other demographic groups. Next year’s dataset will be even richer than this year’s dataset because we will have a full year of data generated by the largest fifteen law enforcement agencies in California to evaluate. We hope to use the analyses produced this year and those we plan to undertake in the coming years to make policy recommendations that law enforcement can adopt to help identify and eradicate unlawful profiling. The Board will continue with its important charge to evaluate and make recommendations surrounding racial and identity profiling and looks to the future with cause for hope. California communities, law enforcement and the public alike have rallied together to take a meaningful look at these issues since the Board was formed in 2016. Through the work of the Board, diverse stakeholders have come together to collectively develop solutions to cultivate trust and strengthen law enforcement- community relations. 96