These data on 19th- and early 20th-century police department and arrest behavior were collected between 1975 and 1978 for a study of police and crime in the United States. Raw and aggregated time-series data are presented in Parts 1 and 3 on 23 American cities for most years during the period 1860-1920. The data were drawn from annual reports of police departments found in the Library of Congress or in newspapers and legislative reports located elsewhere. Variables in Part 1, for which the city is the unit of analysis, include arrests for drunkenness, conditional offenses and homicides, persons dismissed or held, police personnel, and population. Part 3 aggregates the data by year and reports some of these variables on a per capita basis, using a linear interpolation from the last decennial census to estimate population. Part 2 contains data for 267 United States cities for the period 1880-1890 and was generated from the 1880 federal census volume, REPORT ON THE DEFECTIVE, DEPENDENT, AND DELINQUENT CLASSES, published in 1888, and from the 1890 federal census volume, SOCIAL STATISTICS OF CITIES. Information includes police personnel and expenditures, arrests, persons held overnight, trains entering town, and population.

Law Enforcement Locations Any _location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been

To ensure an accurate sampling frame for its Law Enforcement Management and Administrative Statistics (LEMAS) survey, the Bureau of Justice Statistics periodically sponsors a census of the nation's state and local law enforcement agencies. This census, known as the Directory Survey, gathers data on 49 primary state law enforcement agencies and all sheriffs' departments, local police departments, and special police agencies (state or local) that are publicly funded and employ at least one sworn officer with general arrest powers. The 1996 Directory Survey collected data on the number of sworn and nonsworn personnel employed by each agency, including both full-time and part-time employees. Within the full-time sworn category, data were collected from all agencies on the number who were uniformed officers with regularly assigned duties that included responding to calls for service. For agencies with at least 10 full-time sworn officers, the number whose primary duties were related to investigations, court operations, or jail operations was also obtained. This data collection, compiled in June 1996, represents the third such census, with the first occurring in 1986 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1986: [UNITED STATES] [ICPSR 8696]) and the second in 1992 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1992: [UNITED STATES] [ICPSR 2266]). Variables include personnel totals, type of government, type of agency, and whether the agency had the legal authority to hold a person beyond arraignment for 48 or more hours.

This study surveyed police chiefs and data analysts in order to determine the use of data in police departments. The surveys were sent to 1,379 police agencies serving populations of at least 25,000. The survey sample for this study was selected from the 2000 Law Enforcement Management and Administrative Statistics (LEMAS) survey. All police agencies serving populations of at least 25,000 were selected from the LEMAS database for inclusion. Separate surveys were sent for completion by police chiefs and data analysts. Surveys were used to gather information on data sharing and integration efforts to identify the needs and capacities for data usage in local law enforcement agencies. The police chief surveys focused on five main areas of interest: use of data, personnel response to data collection, the collection and reporting of incident-based data, sharing data, and the providing of statistics to the community and media. Like the police chief surveys, the data analyst surveys focused on five main areas of interest: use of data, agency structures and resources, data for strategies, data sharing and outside assistance, and incident-based data. The final total of police chief surveys included in the study is 790, while 752 data analyst responses are included.

The BJS Census of State and Local Law Enforcement Agencies (CSLLEA) is conducted every 4 years to provide a complete enumeration of agencies and their employees. Employment data are reported by agencies for sworn and nonsworn (civilian) personnel and, within these categories, by full-time or part-time status. The pay period that included September 30, 2008, was the reference date for all personnel data. Agencies also complete a checklist of functions they regularly perform, or have primary responsibility for, within the following areas: patrol and response, criminal investigation, traffic and vehicle-related functions, detention-related functions, court-related functions, special public safety functions (e.g., animal control), task force participation, and specialized functions (e.g., search and rescue). The CSLLEA provides national data on the number of state and local law enforcement agencies and employees for local police departments, sheriffs' offices, state law enforcement agencies, and special jurisdiction agencies. It also serves as the sampling frame for BJS surveys of law enforcement agencies.

The purpose of the study was to investigate how and why injuries occur to police and citizens during use of force events. The research team conducted a national survey (Part 1) of a stratified random sample of United States law enforcement agencies regarding the deployment of, policies for, and training with less lethal technologies. Finalized surveys were mailed in July 2006 to 950 law enforcement agencies, and a total of 518 law enforcement agencies provided information on less lethal force generally and on their deployment and policies regarding conducted energy devices (CEDs) in particular. A total of 292 variables are included in the National Use of Force Survey Data (Part 1) including items about weapons deployment, force policies, training, force reporting/review, force incidents and outcomes, and conducted energy devices (CEDs). Researchers also collected agency-supplied use of force data from law enforcement agencies in Richland County, South Carolina; Miami-Dade, Florida; and Seattle, Washington; to identify individual and situational predictors of injuries to officers and citizens during use of force events. The Richland County, South Carolina Data (Part 2) include 441 use-of-force reports from January 2005 through July 2006. Part 2 contains 17 variables including whether the officer or suspect was injured, 8 measures of officer force, 3 measures of suspect resistance, the number of witnesses and officers present at each incident, and the number of suspects that resisted or assaulted officers for each incident. The Miami-Dade County, Florida Data (Part 3) consist of 762 use-of-force incidents that occurred between January 2002 and May 2006. Part 3 contains 15 variables, including 4 measures of officer force, the most serious resistance on the part of the suspect, whether the officer or suspect was injured, whether the suspect was impaired by drugs or alcohol, the officer's length of service in years, and several demographic variables pertaining to the suspect and officer. The Seattle, Washington Data (Part 4) consist of 676 use-of-force incidents that occurred between December 1, 2005, as 15 variables, including 3 measures of officer force, whether the suspect or officer was injured, whether the suspect was impaired by drugs or alcohol, whether the suspect used, or threatened to use, physical force against the officer(s), and several demographic variables relating to the suspect and officer(s). The researchers obtained use of force survey data from several large departments representing different types of law enforcement agencies (municipal, county, sheriff's department) in different states. The research team combined use of force data from multiple agencies into a single dataset. This Multiagency Use of Force Data (Part 5) includes 24,928 use-of-force incidents obtained from 12 law enforcement agencies from 1998 through 2007. Part 5 consists a total of 21 variables, including the year the incident took place, demographic variables relating to the suspect, the type of force used by the officer, whether the suspect or officer was injured, and 5 measures of the department's policy regarding the use of CEDs and pepper spray. Lastly, longitudinal data were also collected for the Orlando, Florida and Austin, Texas police departments. The Orlando, Florida Longitudinal Data (Part 6) comprise 4,222 use-of-force incidents aggregated to 108 months -- a 9 year period from 1998 through 2006. Finally, the Austin, Texas Longitudinal Data (Part 7) include 6,596 force incidents aggregated over 60 months- a 5 year period from 2002 through 2006. Part 6 and Part 7 are comprised of seven variables documenting whether a Taser was implemented, the number of suspects and officers injured in a month, the number of force incidents per month, and the number of CEDs uses per month.

This is five years of police use of force data for all 468 New Jersey municipal police departments and the New Jersey State Police compiled by NJ Advance Media for The Force Report.

When police punch, pepper spray or use other force against someone in New Jersey, they are required to fill out a form detailing what happened. NJ Advance Media filed 506 public records requests and received 72,607 forms covering 2012 through 2016. For more data collection details, see our Methodology here. Data cleaning details can be found here.

We then cleaned, analyzed and compiled the data by department to get a better look at what departments were using the most force, what type of force they were using, and who they were using it on. The result, our searchable database, can be found at NJ.com/force. But we wanted to make department-level results — our aggregate data — available in another way to the broader public.

Below you'll find two files:

• UOF_BY_DEPARTMENTS.csv, with every department's summary data, including the State Police. (This is important to note because the State Police patrols multiple towns and may not be comparable to other departments.)
• UOF_STATEWIDE.csv, a statewide summary of the same data.

For more details on individual columns, see the data dictionary for UOF_BY_DEPARTMENTS. We have also created sample SQL queries to make it easy for users to quickly find their town or county.

It's important to note that these forms were self-reported by police officers, sometimes filled out by hand, so even our data cleaning can't totally prevent inaccuracies from cropping up. We've also included comparisons to population data (from the Census) and arrest data (from the FBI Uniform Crime Report), to try to help give context to what you're seeing.

What about the form-level data?

We have included individual incidents on each department page, but we are not publishing the form-level data freely to the public. Not only is that data extremely dirty and difficult to analyze — at least, it took us six months — but it contains private information about subjects of force, including minors and people with mental health issues. However, we are planning to make a version of that file available upon request in the future.

Data analysis FAQ

What are rows? What are incidents?
Every time any police officer uses force against a subject, they must fill out a form detailing what happened and what force they used. But sometimes multiple police officers used force against the same subject in the same incident. "Rows" are individual forms officers filled out, "incidents" are unique incidents based on the incident number and date.

What are the odds ratios, and how did you calculate them?
We wanted a simple way of showing readers the disparity between black and white subjects in a particular town. So we used an odds ratio, a statistical method often used in research to compare the odds of one thing happening to another. For population, the calculation was (Number of black subjects/Total black population of area)/(Number of white subjects/Total white population of area). For arrests, the calculation was (Number of black subjects/Total number of black arrests in area)/(Number of white subjects/Total number of white arrests in area). In addition, when we compared anything to arrests, we took out all incidents where the subject was an EDP (emotionally disturbed person).

What are the NYC/LA/Chicago warning systems?
Those three departments each look at use of force to flag officers if they show concerning patterns, as way to select those that could merit more training or other action by the department. We compared our data to those three systems to see how many officers would trigger the early warning systems for each. Here are the three systems: - In New York City, officers are flagged for review if they use higher levels of force — including a baton, Taser or firearm, but not pepper spray — or if anyone was injured or hospitalized. We calculated this number by identifying every officer who met one or more of the criteria. - In Los Angeles, officers are compared with one another based on 14 variables, including use of force. If an officer ranks significantly higher than peers for any of the variables — technically, 3 standards of deviation from the norm — supervisors are automatically notified. We calculated this number conservatively by using only use of force as a variable over the course of a calendar year. - In Chicago, officers are flagged for review if force results in an injury or hospitalization, or if the officer uses any level of force above punches or kicks. We calculated this number by identifying every officer who met one or more of the criteria.

What are the different levels of force?
Each officer was required to include in the form what type of force they used against a subject. We cleaned and standardized the data to major categories, although officers could write-in a different type of force if they wanted to. Here are the major categories: - Compliance hold: A compliance hold is a painful maneuver using pressure points to gain control over a suspect. It is the lowest level of force and the most commonly used. But it is often used in conjunction with other types of force. - Takedown: This technique is used to bring a suspect to the ground and eventually onto their stomach to cuff them. It can be a leg sweep or a tackle. - Hands/fist: Open hands or closed fist strikes/punches. - Leg strikes: Leg strikes are any kick or knee used on a subject. - Baton: Officers are trained to use a baton when punches or kicks are unsuccessful. - Pepper spray: Police pepper spray, a mist derived from the resin of cayenne pepper, is considered “mechanical force” under state guidelines. - Deadly force: The firing of an officer's service weapon, regardless of whether a subject was hit. “Warning shots” are prohibited, and officers are instructed not to shoot just to maim or subdue a suspect.

Chicago Police district station locations and contact information.

Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes are included due to the fact that the New Mexico Mounted Police work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 08/14/2006 and the newest record dates from 10/23/2009

Context:

On a typical day in the United States, police officers make more than 50,000 traffic stops. The Stanford Open Policing Project team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Their goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.

If you'd like to see data regarding other states, please go to https://www.kaggle.com/stanford-open-policing.

Content:

This dataset includes over 1 gb of stop data from Ohio. Please see the data readme for the full details of the available fields.

Acknowledgements:

This dataset was kindly made available by the Stanford Open Policing Project. If you use it for a research publication, please cite their working paper: E. Pierson, C. Simoiu, J. Overgoor, S. Corbett-Davies, V. Ramachandran, C. Phillips, S. Goel. (2017) “A large-scale analysis of racial disparities in police stops across the United States”.

Inspiration:

• How predictable are the stop rates? Are there times and places that reliably generate stops?
• Concerns have been raised about jurisdictions using civil forfeiture as a funding mechanism rather than to properly fight drug trafficking. Can you identify any jurisdictions that may be exhibiting this behavior?

Investigator(s): Bureau of Justice Statistics In 1995, to determine the nature of law enforcement services provided on campus, the Bureau of Justice Statistics (BJS) surveyed four-year institutions of higher education in the United States with 2,500 or more students. This survey describes nearly 600 of these campus law enforcement agencies in terms of their personnel, expenditures and pay, operations, equipment, computers and information systems, policies, and special programs. The survey was based on the BJS Law Enforcement Management and Administrative Statistics (LEMAS) program, which collected similar data from a national sample of state and local law enforcement agencies.

This study was undertaken to provide current information on work and family issues from the police officer's perspective, and to explore the existence and prevalence of work and family training and intervention programs offered nationally by law enforcement agencies. Three different surveys were employed to collect data for this study. First, a pilot study was conducted in which a questionnaire, designed to elicit information on work and family issues in law enforcement, was distributed to 1,800 law enforcement officers representing 21 municipal, suburban, and rural police agencies in western New York State (Part 1). Demographic information in this Work and Family Issues in Law Enforcement (WFILE) questionnaire included the age, gender, ethnicity, marital status, highest level of education, and number of years in law enforcement of each respondent. Respondents also provided information on which agency they were from, their job title, and the number of children and step-children they had. The remaining items on the WFILE questionnaire fell into one of the following categories: (1) work and family orientation, (2) work and family issues, (3) job's influence on spouse/significant other, (4) support by spouse/significant other, (5) influence of parental role on the job, (6) job's influence on relationship with children, (7) job's influence on relationships and friendships, (8) knowledge of programs to assist with work and family issues, (9) willingness to use programs to assist with work and family issues, (10) department's ability to assist officers with work and family issues, and (11) relationship with officer's partner. Second, a Police Officer Questionnaire (POQ) was developed based on the results obtained from the pilot study. The POQ was sent to over 4,400 officers in police agencies in three geographical locations: the Northeast (New York City, New York, and surrounding areas), the Midwest (Minneapolis, Minnesota, and surrounding areas), and the Southwest (Dallas, Texas, and surrounding areas) (Part 2). Respondents were asked questions measuring their health, exercise, alcohol and tobacco use, overall job stress, and the number of health-related stress symptoms experienced within the last month. Other questions from the POQ addressed issues of concern to the Police Research and Education Project -- a sister organization of the National Association of Police Organizations -- and its membership. These questions dealt with collective bargaining, the Law Enforcement Officer's Bill of Rights, residency requirements, and high-speed pursuit policies and procedures. Demographic variables included gender, age, ethnicity, marital status, highest level of education, and number of years employed in law enforcement. Third, to identify the extent and nature of services that law enforcement agencies provided for officers and their family members, an Agency Questionnaire (AQ) was developed (Part 3). The AQ survey was developed based on information collected from previous research efforts, the Violent Crime Control and Law Enforcement Act of 1994 (Part W-Family Support, subsection 2303 [b]), and from information gained from the POQ. Data collected from the AQ consisted of whether the agency had a mission statement, provided any type of mental health service, and had a formalized psychological services unit. Respondents also provided information on the number of sworn officers in their agency and the gender of the officers. The remaining questions requested information on service providers, types of services provided, agencies' obstacles to use of services, agencies' enhancement of services, and the organizational impact of the services.

Law Enforcement Locations in Utah Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS is deleting these locations as we become aware of them, but some probably still exist in this dataset. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to fact that many constables work out of their home. FBI entites are intended to be excluded from this dataset, but a few may be included. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2013/05/20Last Update: March 6, 2014

The purpose of this study was to describe the dynamics of police research, how the role and practice of research differ among police agencies, and why this appears to happen. This study also attempts to answer, on a national scale, four fundamental questions: (1) What is police research? (2) Who does it? (3) Why is it done? and (4) What impact does it have? In addition to describing the overall contours of the conduct of research in United States police agencies, this study also sought to explore the organizational dynamics that might contribute to understanding the different roles research plays in various types of police organizations. Questionnaires were mailed in 1990 to 777 sheriff, municipal, county, and state police agencies selected for this study, resulting in 491 surveys for analysis. Respondents were asked to identify the extent to which they were involved in each of 26 distinct topic areas within the past year, to specify the five activities that consumed most of their time during the previous year, and to describe briefly any projects currently being undertaken that might be of interest to other police agencies. A second approach sought to describe police research not in terms of the topics studied but in terms of the methods police used to study those topics. A third section of the questionnaire called for respondents to react to a series of statements characterizing the nature of research as practiced in their agencies. A section asking respondents to describe the characteristics of those responsible for research in their agency followed, covering topics such as to whom the research staff reported. Respondent agencies were also asked to evaluate the degree to which various factors played a role in initiating research in their agencies. Finally, questions about the impact of research on the police agency were posed.

Feature layer showing the locations of Sworn Law Enforcement Officer Locations in California.This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. This also applies to mounted police in New Mexico. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection in the United States and its territories. This dataset is comprised completely of license free data. At the request of NGA, FBI entities are intended to be excluded from this dataset, but a few may be included. The HSIP Freedom Law Enforcement dataset and the HSIP Freedom Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Please see the process description for the breakdown of how the records were merged. With the merge of the Law Enforcement and the Correctional Institutions datasets, the HSIP Themes and NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard HSIP fields that TGS populated. Double spaces were replaced by single spaces in these same fields. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 12/07/2004 and the newest record dates from 09/10/2009.Use Cases: Use cases describe how the data may be used and help to define and clarify requirements.1. An assessment of whether or not the total police capability in a given area is adequate. 2. A list of resources to draw upon in surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can help to determine those entities who are able to respond the quickest. 3. A resource for emergency management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for federal government events.

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.

🇺🇸 United States English This dataset reflects incidents that have been reported to the New Orleans Police Department in 2023. Data is provided by Orleans Parish Communication District (OPCD), the administrative office of 9-1-1 for the City of New Orleans. Please request 911 audio via our public records request system here: https://nola.nextrequest.com. In the OPCD system, NOPD may reclassify or change the signal type for up to 36 hours after the incident is marked up. For information about an incident after this time period, citizens may request police reports from the NOPD Public Records Division. In order to protect the privacy of victims, addresses are shown at the block level and the call types cruelty to juveniles, juvenile attachment and missing juvenile have been removed in accordance with the Louisiana Public Records Act, L.R.S. 44:1. Map coordinates (X,Y) have been removed for the following call types: Aggravated Rape, Aggravated Rape - MA, Crime Against Nature, Mental Patient, Oral Sexual Battery, Prostitution, Sexual Battery, Simple Rape, Simple Rape - Male V, and Soliciting for Prost. Disclaimer: These incidents may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the New Orleans Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The New Orleans Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The New Orleans Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of New Orleans or New Orleans Police Department web page. The user specifically acknowledges that the New Orleans Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. Any use of the information for commercial purposes is strictly prohibited. The unauthorized use of the words "New Orleans Police Department," "NOPD," or any colorable imitation of these words or the unauthorized use of the New Orleans Police Department logo is unlawful. This web page does not, in any way, authorize such use.

The primary objective of this study was to formulate evidence-based lessons on recruitment, retention, and managing workforce profiles in large, United States police departments. The research team conducted a national survey of all United States municipal police agencies that had at least 300 sworn officers and were listed in the 2007 National Directory of Law Enforcement Administrators. The survey instrument was developed based on the research team's experience in working with large personnel systems, instruments used in previous police staffing surveys, and discussions with police practitioners. The research team distributed the initial surveys on February 27, 2008. To ensure an acceptable response rate, the principal investigators developed a comprehensive nonresponse protocol, provided ample field time for departments to compile information and respond, and provided significant one-on-one technical assistance to agencies as they completed the survey. In all, the surveys were in the field for 38 weeks. Respondents were asked to consult their agency's records in order to provide information about their agency's experience with recruiting, hiring, and retaining officers for 2006 and 2007. Of the 146 departments contacted, 107 completed the survey. The police recruitment and retention survey data were supplemented with data on each jurisdiction from the American Community Survey conducted by the United States Census Bureau, the Bureau of Labor Statistics, and the Federal Bureau of Investigation Uniform Crime Reports. The dataset contains a total of 535 variables pertaining to recruitment, hiring, union activity, compensation rates, promotion, retirement, and attrition. Many of these variables are available by rank, sex and race.

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.The purpose of the study was to implement a "platform-based" methodology for collecting data about police organizations and the communities they serve with the goals of generating in-depth standardized information about police organizations, personnel and practices and to help move policing in the direction of evidence-based "learning-organizations" by providing judicious feedback to police agencies and policy makers. The research team conducted three web-based Law Enforcement Organizations (LEO) surveys of sworn and civilian law enforcement employees (LEO Survey A Data, n=22,765; LEO Survey B Data, n=15,825; and LEO Survey C Data, n=16,483). The sample was drawn from the 2007 Law Enforcement Management and Administrative Statistics (LEMAS) database. Agencies with 100 to 3,000 sworn police personnel were eligible for participation. To collect data for the Police-Community Interaction (PCI) survey (PCI Data, n=16,659), each week department employees extracted names and addresses of persons who had recent contact with a police officer because of a reported crime incident, traffic accident or traffic stop. Typically, the surveys were completed within two to four weeks of the encounter.

The local law enforcement locations feature class/ shapefile contains point location and tabular information pertaining to a wide range of law enforcement entities in the United States. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Census of State and Local Law Enforcement Agencies (CSLLEA). Unlike the previous version of this dataset, published in 2009, federal level law enforcement agencies are excluded from this effort. Data fusion techniques are utilized to synchronize overlapping yet disparate source data. The primary sources for this effort are the DOJ-BJS CSLLEA from 2008 and the previously mentioned 2009 feature class from Homeland Security Infrastructure Foundation-Level Data (HIFLD). This feature class contains data for agencies across all 50 U.S. states, Washington D.C. and Puerto Rico.