The areas of focus include: Victimisation, Police Activity, Defendants and Court Outcomes, Offender Management, Offender Characteristics, Offence Analysis, and Practitioners.
This is the latest biennial compendium of Statistics on Ethnicity and the Criminal Justice System and follows on from its sister publication Statistics on Women and the Criminal Justice System, 2019.
Biennial statistics on the representation of Black, Asian and Minority Ethnic groups as victims, suspects, offenders and employees in the Criminal Justice System.
These reports are released by the Ministry of Justice and produced in accordance with arrangements approved by the UK Statistics Authority.
This report provides information about how members of Black, Asian and Minority Ethnic (BME) Groups in England and Wales were represented in the Criminal Justice System (CJS) in the most recent year for which data were available, and, wherever possible, across the last five years. Section 95 of the Criminal Justice Act 1991 requires the Government to publish statistical data to assess whether any discrimination exists in how the CJS treats people based on their race.
These statistics are used by policy makers, the agencies who comprise the CJS and others to monitor differences between ethnic groups and where practitioners and others may wish to undertake more in-depth analysis. The identification of differences should not be equated with discrimination as there are many reasons why apparent disparities may exist.
The most recent data on victims showed differences in the risks of crime between ethnic groups and, for homicides, in the relationship between victims and offenders. Overall, the number of racist incidents and racially or religiously aggravated offences recorded by the police had decreased over the last five years. Key Points:
Per 1,000 population, higher rates of s1 Stop and Searches were recorded for all BME groups (except for Chinese or Other) than for the White group. While there were decreases across the last five years in the overall number of arrests and in arrests of White people, arrests of those in the Black and Asian group increased.
Data on out of court disposals and court proceedings show some differences in the sanctions issued to people of differing ethnicity and also in sentence lengths. These differences are likely to relate to a range of factors including variations in the types of offences committed and the plea entered, and should therefore be treated with caution. Key points:
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This dataset contains the yearly statistics of the race, ethnicity and age of the Known Offenders. Age is further categorized as above 18 and under 18. Here Known Offenders indicates that some aspects of the suspect are identified, thus distinguishing from an unknown offender.
The areas of focus include: Victimisation, Police Activity, Defendants and Court Outcomes, Offender Management, Offender Characteristics, Offence Analysis, and Practitioners.
This is the latest biennial compendium of Statistics on Race and the Criminal Justice System and follows on from its sister publication Statistics on Women and the Criminal Justice System, 2017.
This publication compiles statistics from data sources across the Criminal Justice System (CJS), to provide a combined perspective on the typical experiences of different ethnic groups. No causative links can be drawn from these summary statistics. For the majority of the report no controls have been applied for other characteristics of ethnic groups (such as average income, geography, offence mix or offender history), so it is not possible to determine what proportion of differences identified in this report are directly attributable to ethnicity. Differences observed may indicate areas worth further investigation, but should not be taken as evidence of bias or as direct effects of ethnicity.
In general, minority ethnic groups appear to be over-represented at many stages throughout the CJS compared with the White ethnic group. The greatest disparity appears at the point of stop and search, arrests, custodial sentencing and prison population. Among minority ethnic groups, Black individuals were often the most over-represented. Outcomes for minority ethnic children are often more pronounced at various points of the CJS. Differences in outcomes between ethnic groups over time present a mixed picture, with disparity decreasing in some areas are and widening in others.
In 2023, 8,842 murderers in the United States were white, while 6,405 were Black. A further 461 murderers were of another race, including American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander. However, not all law enforcement agencies submitted homicide data to the FBI in 2023, meaning there may be more murder offenders of each race than depicted. While the majority of circumstances behind murders in the U.S. are unknown, narcotics, robberies, and gang killings are most commonly identified.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This publication fulfils a statutory obligation for the Secretary of State to publish, annually, information relating to the criminal justice system with reference to avoiding discrimination on the ground of race. The publication reports statistical information on the representation of black and minority ethnic groups as suspects, offenders and victims within the criminal justice system and on employees within criminal justice agencies.
Source agency: Justice
Designation: National Statistics
Language: English
Alternative title: Race and the CJS
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This dataset contains the yearly statistics on the race and ethnicity of known offenders by type of offense. Major categories of bias motivations include Race/Ethnicity/Ancestry, Religion, Sexual Orientation, Disability, Gender and Gender Identity. Here Known Offenders indicates that some aspects of the suspect are identified, thus distinguishing from an unknown offender.
Section 95 of the Criminal Justice Act 1991 requires the Government to publish statistical data to assess whether any discrimination exists in how the CJS treats individuals based on their ethnicity.
These statistics are used by policy makers, the agencies who comprise the CJS and others (e.g. academics, interested bodies) to monitor differences between ethnic groups, and to highlight areas where practitioners and others may wish to undertake more in-depth analysis. The identification of differences should not be equated with discrimination as there are many reasons why apparent disparities may exist. The main findings are:
The 2012/13 Crime Survey for England and Wales shows that adults from self-identified Mixed, Black and Asian ethnic groups were more at risk of being a victim of personal crime than adults from the White ethnic group. This has been consistent since 2008/09 for adults from a Mixed or Black ethnic group; and since 2010/11 for adults from an Asian ethnic group. Adults from a Mixed ethnic group had the highest risk of being a victim of personal crime in each year between 2008/09 and 2012/13.
Homicide is a rare event, therefore, homicide victims data are presented aggregated in three-year periods in order to be able to analyse the data by ethnic appearance. The most recent period for which data are available is 2009/10 to 2011/12.
The overall number of homicides has decreased over the past three three-year periods. The number of homicide victims of White and Other ethnic appearance decreased during each of these three-year periods. However the number of victims of Black ethnic appearance increased in 2006/07 to 2008/09 before falling again in 2009/10 to 2011/12.
For those homicides where there is a known suspect, the majority of victims were of the same ethnic group as the principal suspect. However, the relationship between victim and principal suspect varied across ethnic groups. In the three-year period from 2009/10 to 2011/12, for victims of White ethnic appearance the largest proportion of principal suspects were from the victim’s own family; for victims of Black ethnic appearance, the largest proportion of principal suspects were a friend or acquaintance of the victim; while for victims of Asian ethnic appearance, the largest proportion of principal suspects were strangers.
Homicide by sharp instrument was the most common method of killing for victims of White, Black and Asian ethnic appearance in the three most recent three-year periods. However, for homicide victims of White ethnic appearance hitting and kicking represented the second most common method of killing compared with shooting for victims of Black ethnic appearance, and other methods of killing for victims of Asian ethnic appearance.
In 2011/12, a person aged ten or older (the age of criminal responsibility), who self-identified as belonging to the Black ethnic group was six times more likely than a White person to be stopped and searched under section 1 (s1) of the Police and Criminal Evidence Act 1984 and other legislation in England and Wales; persons from the Asian or Mixed ethnic group were just over two times more likely to be stopped and searched than a White person.
Despite an increase across all ethnic groups in the number of stops and searches conducted under s1 powers between 2007/08 and 2011/12, the number of resultant arrests decreased across most ethnic groups. Just under one in ten stop and searches in 2011/12 under s1 powers resulted in an arrest in the White and Black self-identified ethnic groups, compared with 12% in 2007/08. The proportion of resultant arrests has been consistently lower for the Asian self-identified ethnic group.
In 2011/12, for those aged 10 or older, a Black person was nearly three times more likely to be arrested per 1,000 population than a White person, while a person from the Mixed ethnic group was twice as likely. There was no difference in the rate of arrests between Asian and White persons.
The number of arrests decreased in each year between 2008/09 and 2011/12, consistent with a downward trend in police recorded crime since 2004/05. Overall, the number of arrests decreased for all ethnic groups between 2008/09 and 2011/12, however arrests of suspects from the Black, Asian and Mixed ethnic groups peaked in 2010/11.
Arrests for drug offences and sexual offences increased for suspects in all ethnic groups except the Chinese or Other ethnic group between 2008/09 and 2011/12. In addition, there were increases in arrests for burglary, robbery and the other offences category for suspects from the Black and Asian ethnic groups.
The use of out of court disposals (Penalty Notices for Disorder and caution
During a June 2020 survey, registered voters among varying ethnicities were asked how important they thought it was for Congress to pass a bill to overhaul the criminal justice system. Among the survey participants who identified as African American, 56 percent responded that such a bill should be a top priority for Congress. This was the only ethnic group to have a majority respond with a top priority.
In 2023, the FBI knew of ***** perpetrators of anti-Black or African American hate crimes conducted in the United States in that year. Furthermore, another *** perpetrators of anti-White hate crimes were known to the FBI in that year.
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This Dataset contains year, date of incident, US State and location wise total number of adult and juvenile victims and offenders. The dataset also has data based on offender race, offender ethnicity, offence name, bias description and victim type level
Note: Only those biases which were closely related to Indian context namely Anti-Asian, Anti-Hindu, Anti-Sikh, Anti-Muslim, and Anti-Buddhist were considered in this dataset
In 1980, the National Institute of Justice awarded a grant to the Cornell University College of Human Ecology for the establishment of the Center for the Study of Race, Crime, and Social Policy in Oakland, California. This center mounted a long-term research project that sought to explain the wide variation in crime statistics by race and ethnicity. Using information from eight ethnic communities in Oakland, California, representing working- and middle-class Black, White, Chinese, and Hispanic groups, as well as additional data from Oakland's justice systems and local organizations, the center conducted empirical research to describe the criminalization process and to explore the relationship between race and crime. The differences in observed patterns and levels of crime were analyzed in terms of: (1) the abilities of local ethnic communities to contribute to, resist, neutralize, or otherwise affect the criminalization of its members, (2) the impacts of criminal justice policies on ethnic communities and their members, and (3) the cumulative impacts of criminal justice agency decisions on the processing of individuals in the system. Administrative records data were gathered from two sources, the Alameda County Criminal Oriented Records Production System (CORPUS) (Part 1) and the Oakland District Attorney Legal Information System (DALITE) (Part 2). In addition to collecting administrative data, the researchers also surveyed residents (Part 3), police officers (Part 4), and public defenders and district attorneys (Part 5). The eight study areas included a middle- and low-income pair of census tracts for each of the four racial/ethnic groups: white, Black, Hispanic, and Asian. Part 1, Criminal Oriented Records Production System (CORPUS) Data, contains information on offenders' most serious felony and misdemeanor arrests, dispositions, offense codes, bail arrangements, fines, jail terms, and pleas for both current and prior arrests in Alameda County. Demographic variables include age, sex, race, and marital status. Variables in Part 2, District Attorney Legal Information System (DALITE) Data, include current and prior charges, days from offense to charge, disposition, and arrest, plea agreement conditions, final results from both municipal court and superior court, sentence outcomes, date and outcome of arraignment, disposition, and sentence, number and type of enhancements, numbers of convictions, mistrials, acquittals, insanity pleas, and dismissals, and factors that determined the prison term. For Part 3, Oakland Community Crime Survey Data, researchers interviewed 1,930 Oakland residents from eight communities. Information was gathered from community residents on the quality of schools, shopping, and transportation in their neighborhoods, the neighborhood's racial composition, neighborhood problems, such as noise, abandoned buildings, and drugs, level of crime in the neighborhood, chances of being victimized, how respondents would describe certain types of criminals in terms of age, race, education, and work history, community involvement, crime prevention measures, the performance of the police, judges, and attorneys, victimization experiences, and fear of certain types of crimes. Demographic variables include age, sex, race, and family status. For Part 4, Oakland Police Department Survey Data, Oakland County police officers were asked about why they joined the police force, how they perceived their role, aspects of a good and a bad police officer, why they believed crime was down, and how they would describe certain beats in terms of drug availability, crime rates, socioeconomic status, number of juveniles, potential for violence, residential versus commercial, and degree of danger. Officers were also asked about problems particular neighborhoods were experiencing, strategies for reducing crime, difficulties in doing police work well, and work conditions. Demographic variables include age, sex, race, marital status, level of education, and years on the force. In Part 5, Public Defender/District Attorney Survey Data, public defenders and district attorneys were queried regarding which offenses were increasing most rapidly in Oakland, and they were asked to rank certain offenses in terms of seriousness. Respondents were also asked about the public's influence on criminal justice agencies and on the performance of certain criminal justice agencies. Respondents were presented with a list of crimes and asked how typical these offenses were and what factors influenced their decisions about such cases (e.g., intent, motive, evidence, behavior, prior history, injury or loss, substance abuse, emotional trauma). Other variables measured how often and under what circumstances the public defender and client and the public defender and the district attorney agreed on the case, defendant characteristics in terms of who should not be put on the stand, the effects of Proposition 8, public defender and district attorney plea guidelines, attorney discretion, and advantageous and disadvantageous characteristics of a defendant. Demographic variables include age, sex, race, marital status, religion, years of experience, and area of responsibility.
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License information was derived automatically
White offenders had the highest reoffending rate out of all ethnic groups (26.6%) in the year to March 2022.
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This Dataset contains year, date of incident, US State and location wise total number of adult and juvenile victims and offenders. The dataset also has data based on offender race, offender ethnicity, offense name, bias description and victim type level
In the year ended June 2019, European offenders accounted for **** percent of the offenders of sexual assault crime in New Zealand. The number of victim-reported crimes has trended slightly upwards the past few years, with the Canterbury and Counties/Manukau regions reporting the highest number of offences across the country.
A large body of multidisciplinary research has documented how sentencing outcomes vary tremendously across racial and ethnic groups. The research challenge lies in establishing whether these sentencing differentials are driven by unobserved heterogeneity correlated to defendant race/ethnicity, or whether they reflect discrimination. We add to the debate by examining the robustness of racial/ethnic sentencing gaps, by gender, when allowing for selection on unobservables. We do so in the context of federal criminal cases, considering 250,000 cases, and using a dataset containing a rich set of covariates relating to defendant and legal characteristics of cases.
This dataset contains detailed information on cases where a hate or bias crime has been reported to the Bloomington Police Department. Hate crimes are criminal offenses motivated by bias against race, religion, ethnicity, sexual orientation, gender identity, or other protected characteristics. This dataset provides insights into the nature and demographics of hate crimes in Bloomington, aiding in understanding and addressing these incidents.
The dataset includes the following columns:
Column Name | Description | API Field Name | Data Type |
---|---|---|---|
case_number | Case Number | case_number | Text |
date | Date | date | Floating Timestamp |
weekday | Day of Week | day_of_week | Text |
victims | Total Number of Victims | victims | Number |
victim_race | Victim Race | victim_race | Text |
victim_gender | Victim Gender | victim_gender | Text |
victim_type | Victim Type | victim_type | Text |
offenders | Total Number of Offenders | offenders | Number |
offender_race | Offender Race | offender_race | Text |
offender_gender | Offender Gender | offender_gender | Text |
offense | Offense / Crime | offense | Text |
location_type | Offense / Crime Location Type | location_type | Text |
motivation | Offense/Crime Bias Motivation | motivation | Text |
This dataset can be used for:
In 2022, about 194,164 perpetrators of child abuse in the United States were white. In that same year, about 83,314 perpetrators of child abuse were Hispanic, and 25,092 were of unknown ethnic origin.
Arrest data from the Washington Association of Sheriffs and Police Chiefs (WASPC). Population and demographic data from the U.S. Census Bureau American Community Survey.
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This dataset provides information on the percentage of offenders in adult correctional facilities by ethnicity and admission status (e.g., remand, sentenced custody, or other temporary detention). Percentage calculations exclude records where the ethnic background of the offender is unknown. Data source: Justice Enterprise Information Network (JEIN), Nova Scotia Department of Justice.
The areas of focus include: Victimisation, Police Activity, Defendants and Court Outcomes, Offender Management, Offender Characteristics, Offence Analysis, and Practitioners.
This is the latest biennial compendium of Statistics on Ethnicity and the Criminal Justice System and follows on from its sister publication Statistics on Women and the Criminal Justice System, 2019.