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Enhancing the Research Partnership Between the Albany Police Department and the Finn Institute, 2005-2016 (ICPSR 37820)

Released/updated on: 2020-12-16
Geographic coverage: United States, New York (state), Albany (New York)
Time period: 2005-01-01--2016-01-01

The Finn Institute is an independent, not-for-profit corporation that conducts research on matters of public safety and security. The project provided for steps that would strengthen and enhance an existing police-researcher partnership, focused around analyses of proactive policing. As part of a research partnership with the Albany Police Department (APD) and the Finn Institute, this study was oriented around a basic research question: can proactive policing be conducted more efficiently, in the sense that a better ratio of high-value to lower-value stops is achieved, such that the trade-off between crime reduction and police community relations is mitigated.

Albany Resident Survey Dataset (DS1) unit of analysis was individuals. Variables include neighborhood crime and disorder, legitimacy and satisfaction with police service, and direct and vicarious experience with stop and perceptions of stops as a problem. Demographic variables include age, race, education, employment, marital status, and household count.

Management of "Smart Stops" Dataset (DS2) unit of analysis was investigatory stops; variables include records of individual stops, the month and year of the stop, whether the location of the stop was a high-crime location, whether the person stopped (or any of the persons stopped, if multiple people were stopped at one time) were high-risk, and whether the stop resulted in an arrest.

Trends in Proactive Policing Dataset (DS3) unit of analysis was APD officers. Variables include number of stops per quarter; variables include demographics such as officer characteristics such as their assignments, length of service, and gender.

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Project on Policing Neighborhoods in Indianapolis, Indiana, and St. Petersburg, Florida, 1996-1997 (ICPSR 3160)

Released/updated on: 2007-06-01
Geographic coverage: Indiana, United States, St. Petersburg, Florida, Indianapolis
Time period: 1996-01-01--1997-01-01
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 community policing areas [CPA]), and sector. Staffing variables (Part 20) include district, shift, and staffing levels for various shifts. Census data (Part 21) include neighborhood, index of socioeconomic distress, total population, and total white population. District population variables (Part 22) include district and population of district. The aggregated citizen data (Part 23) provide the ride and encounter numbers, number of citizens in the encounter, counts of citizens by their various roles, and by sex, age, race, wealth, if known by the police, under the influence of alcohol or drugs, physically injured, had a weapon, or assaulted the police, counts by type of encounter, and counts of police and citizen actions during the encounter.