This project aimed to develop new insights into offender decision-making in hot spots in New York City, and to test whether these insights could inform interventions to reduce crime in hot spots. There were two phases to the project. In the first phase a set of hypotheses were developed about offender decision-making based on semi-structured interviews with individuals who were currently incarcerated, formerly incarcerated individuals, individuals currently on probation, and community members of high crime areas with no justice-involvement. These interviews suggested several factors worthy of further testing. For instance, offenders believed they were less likely to get away with a crime if they knew more about the officers in their community. That is, when police officers were less anonymous, offenders were less likely to go forward with a crime. In the second phase a field intervention was developed and conducted to test whether reducing officer anonymity might deter crime. Through a randomized controlled trial (RCT) while working with NYPD neighborhood coordination officers, who work in New York City Housing Authority (NYCHA) developments, it was tested whether sending information about officers to residents in housing developments would deter crime in those developments.

This study's purpose was twofold: to investigate the nature of police patrol work in a community policing context and to field-test data collection instruments designed for systematic social observation. The project, conducted in Richmond, Virginia, where its police department was in the third year of a five-year plan to implement community policing, was designed as a case study of one police department's experience with community policing, focusing on officers in the patrol division. A team of eight researchers conducted observations with the police officers in the spring and summer of 1992. A total of 120 officers were observed during 125 observation sessions. Observers accompanied officers throughout their regular work shifts, taking brief field notes on officers' activities and encounters with the public. All of an observed officer's time during the shift was accounted for by either encounters or activities. Within 15 hours of the completion of the ridealong, the observer prepared a detailed narrative account of events that occurred during the ridealong and coded key items associated with these events. The study generated five nested quantitative datasets that can be linked by common variables. Part 1, Ridealong Data, provides information pertinent to the 125 observation sessions or "rides." Part 2, Activity Data, focuses on 5,576 activities conducted by officers when not engaged in encounters. Data in Part 3, Encounter Data, describe 1,098 encounters with citizens during the ridealongs. An encounter was defined as a communication between officers and citizens that took over one minute, involved more than three verbal exchanges between an officer and a citizen, or involved significant physical contact between the officer and citizen. Part 4, Citizen Data, provides data relevant to each of the 1,630 citizens engaged by police in the encounters. Some encounters involved more than one citizen. Part 5, Arrest Data, was constructed by merging Parts 1, 3, and 4, and provides information on 451 encounters that occurred during the ridealongs in which the citizen was suspected of some criminal mischief. All identification variables in this collection were created by the researchers for this project. Variables from Part 1 include date, start time, end time, unit, and beat assignment of the observation session, and the primary officer's and secondary officer's sex, race/ethnicity, years as an officer, months assigned to precinct and beat, hours of community policing training, and general orientation to community policing. Variables in Part 2 specify the time the activity began and ended, who initiated the activity, type, location, and visibility of the activity, involvement of the officer's supervisor during the activity, and if the activity involved problem-solving, or meeting with citizens or other community organizations. Part 3 variables include time encounter began and ended, who initiated the encounter, primary and secondary officer's energy level and mood before the encounter, problem as radioed by dispatcher, and problem as it appeared at the beginning of the encounter and at the end of the encounter. Information on the location of the encounter includes percent of time at initial location, visibility, officer's prior knowledge of the initial location, and if the officer anticipated violence at the scene. Additional variables focus on the presence of a supervisor, other police officers, service personnel, bystanders, and participants, if the officer filed or intended to file a report, if the officer engaged in problem-solving, and factors that influenced the officer's actions. Citizen information in Part 4 includes sex, age, and race/ethnicity of the citizen, role in the encounter, if the citizen appeared to be of low income, under the use of alcohol or drugs, or appeared to have a mental disorder or physical injury or illness, if the citizen was representing an establishment, if the citizen lived, worked, or owned property

This study aimed to fill a void in the research regarding police behavior by focusing on the formation and creation of cognitive suspicion by officers. The study also examined formal actions (stops) taken by the police pursuant to that suspicion. The study was conducted using observational research methods and collected quantitative and qualitative data on officer suspicion. Data were collected by observers who rode along with patrol officers from April 2002 to November 2002. Field observers used three major data collection instruments in order to gather as much relevant information as possible from a variety of sources and in diverse situations. The Officer Form was an overall evaluation of the officer's decision-making characteristics, Suspicion Forms captured information each time an incident occurred, and a Suspect Form was a compilation of data from the citizen who had the encounter with the officer. Additional documents included informed consent forms, a card detailing the language to be used for the initial contact with citizens, and hourly activity forms. Anytime a suspicion was formed or a formal action was taken after a suspicion was formed, the observer debriefed the officer as to his or her thoughts and elicited the officer's overall rating of the encounter. Data in this collection include general demographic characteristics of the officer and the suspect, as well as the area in which the suspicion was formed. Data was also gathered regarding what led the officer to form a suspicion, and why a person was or was not stopped.

These data were originally collected by New York Police Department officers and record information gathered as a result of stop question and frisk (SQF) encounters during 2006. These data were used in a study carried out, under contract to the New York City Police Foundation, by the Rand Corporation's Center on Quality Policing. The release of the study, "Analysis of Racial Disparities in the New York Police Department's Stop, Question, and Frisk Practices" (Rand Document TR-534-NYCPF, 2007) generated interest in making the data available for secondary analysis. This data collection contains information on the officer's reasons for initiating a stop, whether the stop led to a summons or arrest, demographic information for the person stopped, and the suspected criminal behavior.

This study sought to examine community policing from a street-level officer's point of view. Active community police officers and sheriff's deputies from law enforcement agencies were interviewed about their opinions, experiences with, and attitudes toward community policing. For the study 90 rank-and-file community policing officers from 30 law enforcement agencies throughout the United States were selected to participate in a 40- to 60-minute telephone interview. The survey was comprised of six sections, providing information on: (1) demographics, including the race, gender, age, job title, highest level of education, and union membership of each respondent, (2) a description of the community policing program and daily tasks, with questions regarding the size of the neighborhood in terms of geography and population, work with citizens and community leaders, patrol methods, activities with youth/juveniles, traditional police duties, and agency and supervisor support of community policing, (3) interaction between community policing and non-community policing officers, (4) hours, safety, and job satisfaction, (5) police training, and (6) perceived effectiveness of community policing.

The purpose of the Project on Policing Neighborhoods (POPN) was to provide an in-depth description of how the police and the community interact with each other in a community policing (CP) environment. Research was conducted in Indianapolis, Indiana, in 1996 and in St. Petersburg, Florida, in 1997. Several research methods were employed: systematic observation of patrol officers (Parts 1-4) and patrol supervisors (Parts 5-14), in-person interviews with patrol officers (Part 15) and supervisors (Parts 16-17), and telephone surveys of residents in selected neighborhoods (Part 18). Field researchers accompanied their assigned patrol or supervising officer during all activities and encounters with the public during the shift. Field researchers noted when various activities and encounters with the public occurred during these "ride-alongs," who was involved, and what happened. In the resulting data files coded observation data are provided at the ride level, the activity level (actions that did not involve interactions with citizens), the encounter level (events in which officers interacted with citizens), and the citizen level. In addition to encounters with citizens, supervisors also engaged in encounters with patrol officers. Patrol officers and patrol supervisors in both Indianapolis and St. Petersburg were interviewed one-on-one in a private interviewing room during their regular work shifts. Citizens in the POPN study beats were randomly selected for telephone surveys to determine their views about problems in their neighborhoods and other community issues. Administrative records were used to create site identification data (Part 19) and data on staffing (Part 20). This data collection also includes data compiled from census records, aggregated to the beat level for each site (Part 21). Census data were also used to produce district populations for both sites (Part 22). Citizen data were aggregated to the encounter level to produce counts of various citizen role categories and characteristics and characteristics of the encounter between the patrol officer and citizens in the various encounters (Part 23). Ride-level data (Parts 1, 5, and 10) contain information about characteristics of the ride, including start and end times, officer identification, type of unit, and beat assignment. Activity data (Parts 2, 6, and 11) include type of activity, where and when the activity took place, who was present, and how the officer was notified. Encounter data (Parts 3, 7, and 12) contain descriptive information on encounters similar to the activity data (i.e., location, initiation of encounter). Citizen data (Parts 4, 8, and 13) provide citizen characteristics, citizen behavior, and police behavior toward citizens. Similarly, officer data from the supervisor observations (Parts 9 and 14) include characteristics of the supervising officer and the nature of the interaction between the officers. Both the patrol officer and supervisor interview data (Parts 15-17) include the officers' demographics, training and knowledge, experience, perceptions of their beats and organizational environment, and beliefs about the police role. The patrol officer data also provide the officers' perceptions of their supervisors while the supervisor data describe supervisors' perceptions of their subordinates, as well as their views about their roles, power, and priorities as supervisors. Data from surveyed citizens (Part 18) provide information about their neighborhoods, including years in the neighborhood, distance to various places in the neighborhood, neighborhood problems and effectiveness of police response to those problems, citizen knowledge of, or interactions with, the police, satisfaction with police services, and friends and relatives in the neighborhood. Citizen demographics and geographic and weight variables are also included. Site identification variables (Part 19) include ride and encounter numbers, site beat (site, district, and beat or

This study sought to investigate the attitudes of residents and law enforcement personnel living or working in Allegany County, New York in order to (1) assess community support of law enforcement efforts to collaborate on projects, and (2) determine rural law enforcement agencies' willingness to work together on community policing projects and share resources in such a way as to improve and increase their overall individual and collective effectiveness and efficiency. Community policing, for this study, was defined as any law enforcement strategy designed to improve policy directed toward law enforcement interaction with community groups and citizens. Data were gathered from surveys that were distributed to two groups. First, to determine community perceptions of crime and attitudes toward the development of collaborative community policing strategies, surveys were distributed to the residents of the villages of Alfred and Wellsville and the town of Alfred in Allegany County, New York (Part 1, Community Survey Data). Second, to capture the ideas and perceptions of different types of law enforcement agencies regarding their willingness to share training, communication, and technology, surveys were distributed to the law enforcement agencies of Wellsville, Alfred, the New York State Police substation (located in the town of Wellsville), the county sheriff's department, and the Alfred State College and Alfred University public safety departments (Part 2, Law Enforcement Survey Data). For Part 1 (Community Survey Data), the residents were asked to rate their level of fear of crime, the reason for most crime problems (i.e., gangs, drugs, or unsupervised children), positive and negative contact with police, the presence and overall level of police service in the neighborhoods, and the importance of motor vehicle patrols, foot patrols, crime prevention programs, and traffic enforcement. Respondents were also asked whether they agreed that police should concentrate more on catching criminals (as opposed to implementing community-based programs), and if community policing was a good idea. Demographic data on residents includes their age, sex, whether they had been the victim of a property or personal crime, and the number of years they had lived in their respective communities. Demographic information for Part 2 (Law Enforcement Survey Data) includes the sex, age, and educational level of law enforcement respondents, as well as the number of years they had worked with their respective departments. Respondents were asked if they believed in and would support programs targeted toward youth, adults, the elderly, and merchants. Further queries focused on the number of regular and overtime hours used to train, develop, and implement department programs. A series of questions dealing with degrees of trust between the departments and levels of optimism was also asked to gauge attitudes that might discourage collaboration efforts with other departments on community-oriented programs. Officers were also asked to rate their willingness to work with the other agencies.

These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed. This study interviewed young men living in New York City about their experiences being stopped by the police on the street or in their cars. It examined how experience with the police as well as general evaluations of police policies, practices and behaviors in the respondent's neighborhood shaped views about police legitimacy, and law related behavior, such as compliance with the law and cooperation with legal authorities.

The Institute for Municipal and Regional Policy (IMRP) at Central Connecticut State University, in consultation with the Office of Policy and Management (OPM), has established a Racial Profiling Prohibition Advisory Board to help oversee the design, evaluation, and management of the racial profiling study mandated by PA 12-74, “An Act Concerning Traffic Stop Information.” The IMRP is working with the advisory board and all appropriate parties to enhance the collection and analysis of traffic stop data in Connecticut. Resources for the project are being made available through the National Highway Traffic and Safety Administration (NHTSA) grant, as administered through the Connecticut Department of Transportation. The primary purpose of the project is to monitor and prohibit racial profiling in Connecticut and to comply with NHTSA grant requirements and are outlined below. Analyze current racial profiling law and make recommendations to the Connecticut General Assembly to better align the statute to legislative intent and current best practices. Ensure compliance with the racial profiling law in as efficient, effective, transparent and inclusive a manner possible. Ensure compliance with NHTSA requirements of Section 1906 funding to include: Fund activities to prohibit racial profiling in the enforcement of State laws regulating the use of Federal-aid highways Collect, maintain and provide public access to traffic stop data Evaluate the results of such data; and develop and implement programs to reduce the occurrence of racial profiling, including programs to train law enforcement officers. The Racial Profiling Prohibition Project Advisory Board and the project staff have been meeting since May 2012 in an effort to outline a plan to successfully implement PA 12-74. The focus of this early phase of the project has been to better understand traffic stop data collection in other states. Four working groups were established to advise on various aspects of the process including; the standardized method for collecting, recording, reporting, and analyzing racial profiling data required by PA 12-74 and to accomplish tasks required to complete the Racial Profiling Prohibition Project. For more information contact: Ken Barrone Policy & Research Specialist Institute for Municipal & Regional Policy, Central Connecticut State University Tel: 860.832.1872 or Email: baroneket@ccsu.edu

To explore the idea of community policing and to get an understanding of citizens' policing needs, representatives from the Ada County Sheriff's Office and Boise State University formed a research partnership and conducted surveys of county residents and sheriff's deputies. The county-wide survey of residents (Part 1) was designed to enhance the sheriff's current community policing program and to assist in the deployment of community policing officers by measuring citizens' perceptions and fear of crime, perceptions of deputies, knowledge of sheriff's services, and support for community policing. Questions in the citizen survey focused on feelings of safety in Ada County, such as perception of drugs, gangs, safety of youth, and safety at night, satisfaction with the Sheriff's Office, including ratings of the friendliness and fairness of the department and how well deputies and citizens worked together, attitudes regarding community-oriented policing, such as whether this type of policing would be a good use of resources and would reduce crime, and neighborhood problems, including how problematic auto theft, vandalism, physical decay, and excessive noise were for citizens. Other questions were asked regarding the sheriff's deputy website, including whether citizens would like the site to post current crime reports, and whether the site should have more information about the jail. Respondents were also queried about their encounters with police, including their ratings of recent services they received for traffic violations, requests for service, and visits to the jail, and familiarity with several programs, such as the inmate substance abuse program and the employee robbery prevention program. Demographic variables in the citizen survey include ethnicity, gender, level of schooling, occupation, income, age, and length of time residing in Ada County. The second survey (Part 2), created for the sheriff's deputies, used questions from the citizen survey about the Sheriff's Office service needs. Deputies were asked to respond to questions in the way they thought that citizens would answer these same questions in the citizen survey. The purpose was to investigate the extent to which sheriff's deputies' attitudes mirrored citizens' attitudes about the quality of service.