In 2023, a total of 5,439 white Americans were arrested for arson in the United States in comparison to 1,876 Americans who were Black or African American.

The purpose of this study was to examine the crime of identity theft from the offenders' perspectives. The study employed a purposive sampling strategy. Researchers identified potential interview subjects by examining newspapers (using Lexis-Nexis), legal documents (using Lexis-Nexis and Westlaw), and United States Attorneys' Web sites for individuals charged with, indicted, and/or sentenced to prison for identity theft. Once this list was generated, researchers used the Federal Bureau of Prisons (BOP) Inmate Locator to determine if the individuals were currently housed in federal facilities. Researchers visited the facilities that housed the largest number of inmates on the list in each of the six regions in the United States as defined by the BOP (Western, North Central, South Central, North Eastern, Mid-Atlantic, and South Eastern) and solicited the inmates housed in these prisons. A total of 14 correctional facilities were visited and 65 individuals incarcerated for identity theft or identity theft related crimes were interviewed between March 2006 and February 2007. Researchers used semi-structured interviews to explore the offenders' decision-making processes. When possible, interviews were audio recorded and then transcribed verbatim. Part 1 (Quantitative Data) includes the demographic variables age, race, gender, number of children, highest level of education, and socioeconomic class while growing up. Other variables include prior arrests or convictions and offense type, prior drug use and if drug use contributed to identity theft, if employment facilitated identity theft, if they went to trial or plead to charges, and sentence length. Part 2 (Qualitative Data), includes demographic questions such as family situation while growing up, highest level of education, marital status, number of children, and employment status while committing identity theft crimes. Subjects were asked about prior criminal activity and drug use. Questions specific to identity theft include the age at which the person became involved in identity theft, how many identities he or she had stolen, if they had worked with other people to steal identities, why they had become involved in identity theft, the skills necessary to steal identities, and the perceived risks involved in identity theft.

The Criminal Justice Research Division of the San Diego Association of Governments (SANDAG) received funds from the National Institute of Justice to assist the Regional Auto Theft Task (RATT) force and evaluate the effectiveness of the program. The project involved the development of a computer system to enhance the crime analysis and mapping capabilities of RATT. Following the implementation of the new technology, the effectiveness of task force efforts was evaluated. The primary goal of the research project was to examine the effectiveness of RATT in reducing auto thefts relative to the traditional law enforcement response. In addition, the use of enhanced crime analysis information for targeting RATT investigations was assessed. This project addressed the following research questions: (1) What were the characteristics of vehicle theft rings in San Diego and how were the stolen vehicles and/or parts used, transported, and distributed? (2) What types of vehicles were targeted by vehicle theft rings and what was the modus operandi of suspects? (3) What was the extent of violence involved in motor vehicle theft incidents? (4) What was the relationship between the locations of vehicle thefts and recoveries? (5) How did investigators identify motor vehicle thefts that warranted investigation by the task force? (6) Were the characteristics of motor vehicle theft cases investigated through RATT different than other cases reported throughout the county? (7) What investigative techniques were effective in apprehending and prosecuting suspects involved in major vehicle theft operations? (8) What was the impact of enhanced crime analysis information on targeting decisions? and (9) How could public education be used to reduce the risk of motor vehicle theft? For Part 1 (Auto Theft Tracking Data), data were collected from administrative records to track auto theft cases in San Diego County. The data were used to identify targets of enforcement efforts (e.g., auto theft rings, career auto thieves), techniques or strategies used, the length of investigations, involvement of outside agencies, property recovered, condition of recoveries, and consequences to offenders that resulted from the activities of the investigations. Data were compiled for all 194 cases investigated by RATT in fiscal year 1993 to 1994 (the experimental group) and compared to a random sample of 823 cases investigated through the traditional law enforcement response during the same time period (the comparison group). The research staff also conducted interviews with task force management (Parts 2 and 3, Investigative Operations Committee Initial Interview Data and Investigative Operations Committee Follow-Up Interview Data) and other task force members (Parts 4 and 5, Staff Initial Interview Data and Staff Follow-Up Interview Data) at two time periods to address the following issues: (1) task force goals, (2) targets, (3) methods of identifying targets, (4) differences between RATT strategies and the traditional law enforcement response to auto theft, (5) strategies employed, (6) geographic concentrations of auto theft, (7) factors that enhance or impede investigations, (8) opinions regarding effective approaches, (9) coordination among agencies, (10) suggestions for improving task force operations, (11) characteristics of auto theft rings, (12) training received, (13) resources and information needed, (14) measures of success, and (15) suggestions for public education efforts. Variables in Part 1 include the total number of vehicles and suspects involved in an incident, whether informants were used to solve the case, whether the stolen vehicle was used to buy parts, drugs, or weapons, whether there was a search warrant or an arrest warrant, whether officers used surveillance equipment, addresses of theft and recovery locations, date of theft and recovery, make and model of the stolen car, condition of vehicle when recovered, property recovered, whether an arrest was made, the arresting agency, date of arrest, arrest charges, number and type of charges filed, disposition, conviction charges, number of convictions, and sentence. Demographic variables include the age, sex, and race of the suspect, if known. Variables in Parts 2 and 3 include the goals of RATT, how the program evolved, the role of the IOC, how often the IOC met, the relationship of the IOC and the executive committee, how RATT was unique, why RATT was successful, how RATT could be improved, how RATT was funded, and ways in which auto theft could be reduced. Variables in Parts 4 and 5 include the goals of RATT, sources of information about vehicle thefts, strategies used to solve auto theft cases, location of most vehicle thefts, how motor vehicle thefts were impacted by RATT, impediments to the RATT program, suggestions for improving the program, ways in which auto theft could be reduced, and methods to educate citizens about auto theft. In addition, Part 5 also has variables about the type of officers' training, usefulness of maps and other data, descriptions of auto theft rings in terms of the age, race, and gender of its members, and types of cars stolen by rings.

GapMaps offers advanced and reliable Crime Risk Location Data sourced from Applied Geographic Solutions (AGS), a trusted provider of premium demographic insights with over 20 years of experience. Leveraged by thousands of businesses, AGS use advanced statistical methodologies and a rolling seven-year database of FBI and local agency statistics to provide a highly accurate view of the relative risk of specific crime types for any geographic area empowering organizations to make informed decisions in areas such as insurance, urban planning, and real estate.

The AGS Crime Risk dataset includes: - Standardised indexes for a range of serious crimes against both persons and property such as murder, rape, robbery, assault, burglary, theft, and motor vehicle theft - Aggregate measures of crime risk, including crimes against persons, crimes against property, and overall crime risk, offering a comprehensive overview of an area’s safety. - 5-Year Projections: Added in 2020, these projections enhance the dataset by forecasting future crime risks, providing valuable insights for long-term planning. - High-Resolution Data: Crime risk indexes are available at the block group level, allowing insurers to identify variations in crime risk across specific land uses such as motor vehicle theft from parking structures.

Use cases: 1. Insurance underwriting and risk mitigation. 2. Evaluating the security measures needed to protect employees and customers at retail facilities. 3. The study of the effects of neighborhood crime on wellness and health care outcomes.

Methodology: Crime is tracked for multiple years using both FBI aggregate crime reports and for many parts of the country at the individual incident level. A complex set of statistical models are used to estimate and forecast risk of each individual crime type by using land use data in conjunction with demographic and business characteristics.

These data examine the effects on total crime rates of changes in the demographic composition of the population and changes in criminality of specific age and race groups. The collection contains estimates from national data of annual age-by-race specific arrest rates and crime rates for murder, robbery, and burglary over the 21-year period 1965-1985. The data address the following questions: (1) Are the crime rates reported by the Uniform Crime Reports (UCR) data series valid indicators of national crime trends? (2) How much of the change between 1965 and 1985 in total crime rates for murder, robbery, and burglary is attributable to changes in the age and race composition of the population, and how much is accounted for by changes in crime rates within age-by-race specific subgroups? (3) What are the effects of age and race on subgroup crime rates for murder, robbery, and burglary? (4) What is the effect of time period on subgroup crime rates for murder, robbery, and burglary? (5) What is the effect of birth cohort, particularly the effect of the very large (baby-boom) cohorts following World War II, on subgroup crime rates for murder, robbery, and burglary? (6) What is the effect of interactions among age, race, time period, and cohort on subgroup crime rates for murder, robbery, and burglary? (7) How do patterns of age-by-race specific crime rates for murder, robbery, and burglary compare for different demographic subgroups? The variables in this study fall into four categories. The first category includes variables that define the race-age cohort of the unit of observation. The values of these variables are directly available from UCR and include year of observation (from 1965-1985), age group, and race. The second category of variables were computed using UCR data pertaining to the first category of variables. These are period, birth cohort of age group in each year, and average cohort size for each single age within each single group. The third category includes variables that describe the annual age-by-race specific arrest rates for the different crime types. These variables were estimated for race, age, group, crime type, and year using data directly available from UCR and population estimates from Census publications. The fourth category includes variables similar to the third group. Data for estimating these variables were derived from available UCR data on the total number of offenses known to the police and total arrests in combination with the age-by-race specific arrest rates for the different crime types.

Annual data from the Crime Survey for England and Wales (CSEW) and metal theft offences recorded by the police, including demographic and offence type breakdowns and time series data.

Black people were over twice as likely to be arrested as white people – there were 20.4 arrests for every 1,000 black people, and 9.4 for every 1,000 white people.

In 2022, the most commonly targeted age group by fraudsters was people ages 30 to 39, among whom ******* cases of fraud were reported to the Federal Trade Commission (FTC) in the United States. People aged 60 to 69 were the second most commonly targeted group, with ******* reports of fraud in the same year.

The National Crime Victimization Survey (NCVS), previously called the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. Beginning in 1992, the survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual assault, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected to enable analysis of crime by various subpopulations. This dataset represents the revised concatenated version of the NCVS on a collection year basis for 1992-2016. A collection year contains records from interviews conducted in the 12 months of the given year. Under the collection year format, victimizations are counted in the year the interview is conducted, regardless of the year when the crime incident occurred. The 2016 National Crime Victimization Survey (NCVS) violent and property crime estimates were significantly higher than 2015, but it was not possible to determine the degree to which the change in rates resulted from the sample redesign rather than real changes in U.S. victimization levels. Therefore, the Bureau of Justice Statistics (BJS) examined the 2015 and 2016 victimization rates separately for new and continuing sample counties in the 2016 Criminal Victimization bulletin. The BJS requested that the U.S. Census Bureau create a 2016 revised file with outgoing county interviews from July-December 2015, continuing county interviews from January-June 2016, and all interviews (continuing and new counties) from July-December 2016. In other words, the outgoing 2015 cases replaced the new 2016 cases in the first half of 2016. The files in this study serve as a separate research file to allow data users to make comparisons between 2015, 2016, and 2017 NCVS estimates using a nationally representative sample. It provides a sample that still represents the entire country but does not have the inflated crime rates seen in the new counties in 2016. For additional information on the dataset, please see the documentation for the data from the most current year of the NCVS, ICPSR Study 37296.

This project sought to investigate a possible relationship between sentencing guidelines and family structure in the United States. The research team developed three research modules that employed a variety of data sources and approaches to understand family destabilization and community distress, which cannot be observed directly. These three research modules were used to discover causal relationships between male withdrawal from productive spheres of the economy and resulting changes in the community and families. The research modules approached the issue of sentencing guidelines and family structure by studying: (1) the flow of inmates into prison (Module A), (2) the role of and issues related to sentencing reform (Module B), and family disruption in a single state (Module C). Module A utilized the Uniform Crime Reporting (UCR) Program data for 1984 and 1993 (Parts 1 and 2), the 1984 and 1993 National Correctional Reporting Program (NCRP) data (Parts 3-6), the Urban Institute's 1980 and 1990 Underclass Database (UDB) (Part 7), the 1985 and 1994 National Longitudinal Survey on Youth (NLSY) (Parts 8 and 9), and county population, social, and economic data from the Current Population Survey, County Business Patterns, and United States Vital Statistics (Parts 10-12). The focus of this module was the relationship between family instability, as measured by female-headed families, and three societal characteristics, namely underclass measures in county of residence, individual characteristics, and flows of inmates. Module B examined the effects of statewide incarceration and sentencing changes on marriage markets and family structure. Module B utilized data from the Current Population Survey for 1985 and 1994 (Part 12) and the United States Statistical Abstracts (Part 13), as well as state-level data (Parts 14 and 15) to measure the Darity-Myers sex ratio and expected welfare income. The relationship between these two factors and family structure, sentencing guidelines, and minimum sentences for drug-related crimes was then measured. Module C used data collected from inmates entering the Minnesota prison system in 1997 and 1998 (Part 16), information from the 1990 Census (Part 17), and the Minnesota Crime Survey (Part 18) to assess any connections between incarceration and family structure. Module C focused on a single state with sentencing guidelines with the goal of understanding how sentencing reforms and the impacts of the local community factors affect inmate family structure. The researchers wanted to know if the aspects of locations that lose marriageable males to prison were more important than individual inmate characteristics with respect to the probability that someone will be imprisoned and leave behind dependent children. Variables in Parts 1 and 2 document arrests by race for arson, assault, auto theft, burglary, drugs, homicide, larceny, manslaughter, rape, robbery, sexual assault, and weapons. Variables in Parts 3 and 4 document prison admissions, while variables in Parts 5 and 6 document prison releases. Variables in Part 7 include the number of households on public assistance, education and income levels of residents by race, labor force participation by race, unemployment by race, percentage of population of different races, poverty rate by race, men in the military by race, and marriage pool by race. Variables in Parts 8 and 9 include age, county, education, employment status, family income, marital status, race, residence type, sex, and state. Part 10 provides county population data. Part 11 contains two different state identifiers. Variables in Part 12 describe mortality data and welfare data. Part 13 contains data from the United States Statistical Abstracts, including welfare and poverty variables. Variables in Parts 14 and 15 include number of children, age, education, family type, gender, head of household, marital status, race, religion, and state. Variables in Part 16 cover admission date, admission type, age, county, education, language, length of sentence, marital status, military status, sentence, sex, state, and ZIP code. Part 17 contains demographic data by Minnesota ZIP code, such as age categories, race, divorces, number of children, home ownership, and unemployment. Part 18 includes Minnesota crime data as well as some demographic variables, such as race, education, and poverty ratio.

Stock theft is a persistent and widespread problem affecting farmers in the Eastern Cape Province of South Africa. This study aimed to explore farmers’ perceptions of stock theft in the region. A mixed methods approach was used to collect data. 192 pre-tested questionnaires were collected from a sample of farmers in three districts in the province. The descriptive and chi-square test was used to test the associations between demographic profile statistically, knowledge of stock theft, reported stock theft cases, the economic impact of stock theft, and stock theft control. According to the findings, stock theft is significantly more likely to occur during the winter season (P < 0.05). About 94.8% of farmers are in the communal farming sector in the three districts visited. Furthermore, 81.2% of the respondents believe that the government needs to do more to combat the spread of stock theft. This study also revealed that most respondents (88.6%) agree that branding and tattooing should be made available to all registered farmers, while 53.1% believe that forensic deoxyribonucleic acid should not be used to control stock theft at crime scenes. This study highlights farmers’ perceptions and knowledge of stock theft to enable policymakers to develop targeted interventions and strategies. Policing strategy must be adaptive and technology-driven to fast-track detection, prevention, and reduction of stuck theft crime.

Crime and socioeconomic data for the German Reich and mortality statistics for Prussia at county level for 1871 to 1912.

Topics: A: variables for the entire German Reich (1047 counties)

1. crime data: a) totals of all convicted for crimes and offences per 100000 b) number convicted due to dangerous bodily injury per 100000 c) number convicted due to simple theft per 100000

2. demographic information: a) totals of population of the age of criminal responsibility in the counties for 1885, 1905 and 1910 b) male German-speaking population in 1900 c) female German-speaking population in 1900 d) male, non-German-speaking population in 1900 e) female, non-German-speaking population in 1900 f) primary ethnic groups in 1900

3. data on urbanization: a) total population of the municipalities with more than 2000 residents per county in 1900 b) population in medium-sized cities per county in 1900 c) population in large cities per county in 1900 d) total population per county in 1900 e) typing the counties in city counties (=1) and districts (=2) in 1900

4. Geographic data a) short designation of all counties (1881 to 1912) b) identification number of all counties listed under 4a) c) surface area of the county in square kilometers in 1900

B: variables for Prussia (583 counties) mortality data for 1885, 1886, 1904, 1905 and 1906:

a) totals of deaths (according to sex) for the respective year b) number of deaths due to Tuberculosis (according to sex) for the respective year c) number of deaths due to suicide (according to sex) for the respective year d) number of deaths due to murder and manslaughter (according to sex) for the respective year

The variables for the Prussian counties can be compared with the corresponding counties of the German Reich.

In 2024, there were 301,623 cases filed by the National Crime Information Center (NCIC) where the race of the reported missing person was white. In the same year, 17,097 people whose race was unknown were also reported missing in the United States. What is the NCIC? The National Crime Information Center (NCIC) is a digital database that stores crime data for the United States, so criminal justice agencies can access it. As a part of the FBI, it helps criminal justice professionals find criminals, missing people, stolen property, and terrorists. The NCIC database is broken down into 21 files. Seven files belong to stolen property and items, and 14 belong to persons, including the National Sex Offender Register, Missing Person, and Identify Theft. It works alongside federal, tribal, state, and local agencies. The NCIC’s goal is to maintain a centralized information system between local branches and offices, so information is easily accessible nationwide. Missing people in the United States A person is considered missing when they have disappeared and their location is unknown. A person who is considered missing might have left voluntarily, but that is not always the case. The number of the NCIC unidentified person files in the United States has fluctuated since 1990, and in 2022, there were slightly more NCIC missing person files for males as compared to females. Fortunately, the number of NCIC missing person files has been mostly decreasing since 1998.

Abstract (en): In the late 1970s, the Rand Corporation pioneered a method of collecting crime rate statistics. They obtained reports of offending behavior--types and frequencies of crimes committed--directly from offenders serving prison sentences. The current study extends this research by exploring the extent to which variation in the methodological approach affects prisoners' self-reports of criminal activity. If the crime rates reported in this survey remained constant across methods, perhaps one of the new techniques developed would be easier and/or less expensive to administer. Also, the self-reported offending rate data for female offenders in this collection represents the first time such data has been collected for females. Male and female prisoners recently admitted to the Diagnostic Unit of the Colorado Department of Corrections were selected for participation in the study. Prisoners were given one of two different survey instruments, referred to as the long form and short form. Both questionnaires dealt with the number of times respondents committed each of eight types of crimes during a 12-month measurement period. The crimes of interest were burglary, robbery, assault, theft, auto theft, forgery/credit card and check-writing crimes, fraud, and drug dealing. The long form of the instrument focused on juvenile and adult criminal activity and covered the offender's childhood and family. It also contained questions about the offender's rap sheet as one of the bases for validating the self-reported data. The crime count sections of the long form contained questions about motivation, initiative, whether the offender usually acted alone or with others, and if the crimes recorded included crimes against people he or she knew. Long-form data are given in Part 1. The short form of the survey had fewer or no questions compared with the long form on areas such as the respondent's rap sheet, the number of crimes committed as a juvenile, the number of times the respondent was on probation or parole, the respondent's childhood experiences, and the respondent's perception of his criminal career. These data are contained in Part 2. In addition, the surveys were administered under different conditions of confidentiality. Prisoners given what were called "confidential" interviews had their names identified with the survey. Those interviewed under conditions of anonymity did not have their names associated with the survey. The short forms were all administered anonymously, while the long forms were either anonymous or confidential. In addition to the surveys, data were collected from official records, which are presented in Part 3. The official record data collection form was designed to collect detailed criminal history information, particularly during the measurement period identified in the questionnaires, plus a number of demographic and drug-use items. This information, when compared with the self-reported offense data from the measurement period in both the short and long forms, allows a validity analysis to be performed. In the late 1970s, the Rand Corporation pioneered a method of collecting crime rate statistics. They obtained reports of offending behavior--types and frequencies of crimes committed--directly from offenders serving prison sentences. The current study extends this research by exploring the extent to which variation in the methodological approach affects prisoners' self-reports of criminal activity. Currently, collecting data from prisoners is a costly, labor-intensive effort. If the crime rates reported in this survey remained constant across methods, perhaps one of the new techniques developed would be easier and/or less expensive to administer. Also, the self-reported offending rate data for female offenders in this collection represents the first time such data has been collected for females. Prisoners recently admitted to the Diagnostic Unit of the Colorado Department of Corrections were selected for participation in the study. Prisoners were given one of two different survey instruments, referred to as the long form and short form. The long form of the survey was a 65-page self-administered survey instrument, while the short form consisted of 45 pages. Both the long and short surveys contained questions on the prisoners' involvement in crime during a 12-month measurement period. This "window period" was defined as the month of arrest and the previous 11 months. An individual's "street months" w...

This dataset shows City level data for all over the United States, and has various attributes for different crimes. Cities are shown as Latitude and longitude points. Attributes include murder, manslaughter, violent crimes, arson, motor vehicle theft, property crimes, aggravated assault, burglary, larceny, theft, and rape. Data was provided by the Federal Bureau of Investigation. Source: FBI URL: http://www.fbi.gov/ucr/cius2006/data/table_08.html

The main focus of this research was on identifying the conditions under which public support for rehabilitation varies. A single, multivariate analysis method was used so that the influence of each respondent, criminal, crime, and treatment characterististic could be determined within the context of all other factors. The research also explored differences between global and specific attitudes toward rehabilitation. Data for this study were collected through a mail survey of 1,000 Ohio residents (Part 1). The initial mailing was sent to all 1,000 members of the sample on May 28, 1996. Several followups were conducted, and data collection efforts ended on August 26, 1996. Questionnaire items elicited demographic, experiential, and attitudinal information from each respondent. To assess the potential influence of offender, offense, and treatment characteristics on the respondent's support for rehabilitation, several variables were combined to create a factorial vignette. This method allowed the independent effects of each factor on support for rehabilitation to be determined. The respondents were asked to express their agreement or disagreement with five statements following the vignette: (1) general support for rehabilitation, (2) effectiveness of intervention, (3) basing release decisions on progress in rehabilitation programs, (4) individualizing sentences to fit treatment needs, and (5) expanding treatment opportunities for offenders. Types of offenses included in the vignettes were robbery, burglary, aggravated assault, larceny, motor vehicle theft, fraud, drug sales, and drug use. These offenses were selected since they are well-known to the public, offenders are arrested for these offenses fairly frequently, and the offenses are potentially punishable by a sentence of either prison or probation. Several attributes within the particular offenses in the vignettes were designed to assess the influence of different levels of harm, either financial or physical. Offender characteristics and offense selection for use in the vignettes were weighted by their frequency of arrests as reported in the Federal Bureau of Investigation's 1995 Uniform Crime Report data. A rating of the seriousness of each offense was assigned using a separate survey of 118 undergraduate university students (Part 2), and the resulting seriousness score was used in the analysis of the vignettes. Additional items on the mail survey instrument assessed the respondent's global and specific attitudes toward treatment. Independent variables from the mail survey include the respondent's age, education, income category, sex, race, political party, rating of political conservativism, personal contact with offenders, religious identity salience, religiosity, attitudes toward biblical literalness and religious forgiveness, fear of crime, and victimization. Variables from the vignettes examined whether support for rehabilitation was influenced by offender age, race, sex, type of offense committed, employment status, substance use, prior record, sentence, and treatment program. Global support for rehabilitation was measured by responses to two questions: what the respondent thought the main emphasis in most prisons was (to punish, to rehabilitate, to protect society), and what the main emphasis should be. Items assessed variations in the respondent's attitudes toward rehabilitation by offender's age, sex, and prior record, location of treatment, and the type of treatment provided. Variables from the crime seriousness survey recorded the respondent's rating of various crime events, including assault and robbery (with or without a weapon, with varying degrees of injury, or no injury to the victim), burglary, larceny, and auto theft (with varying values of the property stolen), drug dealing, drug use, and writing bad checks.

The number of rape and sexual assault cases reported to the police in Germany peaked at ****** in 2024 during the period shown here. Previously, the highest number of cases, ******, had been recorded the year before. Based on the definition in criminal law, sexual assault includes rape, as well as other sexually driven physical attacks. Rape is defined as forcing a person to have sex. Increased crime clearance rate The question remains how high the number of unreported cases is. Reasons for not reporting a sexual assault vary among victims. In recent years, the German police reported increasing clearance rates for sexual crimes. In 2022, **** percent of rape and sexual assault cases were solved, compared to **** percent in 2016. In 2023, however this figure dropped to **** percent, perhaps due to the increase in the number of cases. Among males suspected of committing such crimes, over ** percent were young adults aged 18 to 21 years. Types of German police forces German police forces are divided into several different types, which all have clearly established tasks regulated by law. The Federal Criminal Police Office (Bundeskriminalamt, BKA) is often compared to the FBI in the U.S. and investigates federal crimes, such as kidnapping. The Federal Police (Bundespolizei), works in railway stations, at airports, and seaports. They also protect borders, government buildings, and deal with organized crime and terrorism. The criminal police (Kriminalpolizei, Kripo), the only policemen not wearing in uniform in Germany, handle assault, murder, and rape cases, as well as theft. The uniformed police (Schutzpolizei, SchuPo), or beat police, are regularly visible in streets, as they are responsible for traffic safety, among other tasks, and may be approached directly by people in need of assistance or help.

Incident-based crime statistics (actual incidents, rate per 100,000 population, percentage change in rate, unfounded incidents, percent unfounded, total cleared, cleared by charge, cleared otherwise, persons charged, adults charged, youth charged / not charged), by detailed violations (violent, property, traffic, drugs, other Federal Statutes), police services in Ontario, 1998 to 2024.

In response to several high profile, violent crimes by minority males, which were reported by law enforcement officials as being gang-related, Nevada lawmakers enacted an array of anti-gang legislation, much of it drafted by law enforcement personnel. This study attempted to provide answers to the following research questions: (1) How often and under what specific conditions were the various anti-gang statutes used in the prosecution of gang members? (2) How had the passage of anti-gang statutes and the development of the gang prosecution units influenced the use of more conventional charging practices related to gang cases? and (3) Did specialized gang prosecution produce higher rates of convictions, more prison sentences, and longer prison terms for gang offenders? Court monitoring data were collected from both Clark and Washoe counties to document the actual extent and nature of gang crime in both jurisdictions over several years. Variables include the year of the court case, whether the defendant was a gang member, total number of initial charges, whether all charges were dismissed before trial, whether the defendant was convicted of any charge, the length of the prison sentence imposed, whether the defendant was charged with a gang enhancement statute, and whether the defendant was charged with murder, sexual assault, robbery, kidnapping, burglary, auto theft, larceny, a drug offense, a weapon offense, or assault. Demographic variables include the race, sex, and age of the defendant.