100+ datasets found
  1. Number of murder offenders 2023, by race

    • statista.com
    • ai-chatbox.pro
    Updated Nov 7, 2024
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    Statista (2024). Number of murder offenders 2023, by race [Dataset]. https://www.statista.com/statistics/1466623/murder-offenders-in-the-us-by-race/
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    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.

  2. Murder in the U.S.: number of victims in 2023, by race

    • statista.com
    • ai-chatbox.pro
    Updated Nov 7, 2024
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    Statista (2024). Murder in the U.S.: number of victims in 2023, by race [Dataset]. https://www.statista.com/statistics/251877/murder-victims-in-the-us-by-race-ethnicity-and-gender/
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the FBI reported that there were 9,284 Black murder victims in the United States and 7,289 white murder victims. In comparison, there were 554 murder victims of unknown race and 586 victims of another race. Victims of inequality? In recent years, the role of racial inequality in violent crimes such as robberies, assaults, and homicides has gained public attention. In particular, the issue of police brutality has led to increasing attention following the murder of George Floyd, an African American who was killed by a Minneapolis police officer. Studies show that the rate of fatal police shootings for Black Americans was more than double the rate reported of other races. Crime reporting National crime data in the United States is based off the Federal Bureau of Investigation’s new crime reporting system, which requires law enforcement agencies to self-report their data in detail. Due to the recent implementation of this system, less crime data has been reported, with some states such as Delaware and Pennsylvania declining to report any data to the FBI at all in the last few years, suggesting that the Bureau's data may not fully reflect accurate information on crime in the United States.

  3. Data from: Age-by-Race Specific Crime Rates, 1965-1985: [United States]

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Age-by-Race Specific Crime Rates, 1965-1985: [United States] [Dataset]. https://catalog.data.gov/dataset/age-by-race-specific-crime-rates-1965-1985-united-states-b16aa
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    United States
    Description

    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.

  4. Number, percentage and rate of homicide victims, by racialized identity...

    • www150.statcan.gc.ca
    • data.urbandatacentre.ca
    • +2more
    Updated Jul 25, 2024
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    Government of Canada, Statistics Canada (2024). Number, percentage and rate of homicide victims, by racialized identity group, gender and region [Dataset]. http://doi.org/10.25318/3510020601-eng
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    Dataset updated
    Jul 25, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2023.

  5. w

    Statistics on Race and the Criminal Justice System 2012

    • gov.uk
    Updated Dec 18, 2013
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    Ministry of Justice (2013). Statistics on Race and the Criminal Justice System 2012 [Dataset]. https://www.gov.uk/government/statistics/statistics-on-race-and-the-criminal-justice-system-2012
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    Dataset updated
    Dec 18, 2013
    Dataset provided by
    GOV.UK
    Authors
    Ministry of Justice
    Description

    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:

    Victims of crime

    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 victims

    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.

    Suspects

    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.

    Defendants

    The use of out of court disposals (Penalty Notices for Disorder and caution

  6. C

    Violence Reduction - Victim Demographics - Aggregated

    • data.cityofchicago.org
    • s.cnmilf.com
    application/rdfxml +5
    Updated Jun 24, 2025
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    City of Chicago (2025). Violence Reduction - Victim Demographics - Aggregated [Dataset]. https://data.cityofchicago.org/Public-Safety/Violence-Reduction-Victim-Demographics-Aggregated/gj7a-742p
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    application/rssxml, csv, json, application/rdfxml, xml, tsvAvailable download formats
    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    City of Chicago
    Description

    This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

    This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

    The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

    How does this dataset classify victims?

    The methodology by which this dataset classifies victims of violent crime differs by victimization type:

    Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

    To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

    For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

    1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
    2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

    Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

    1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

    Note: All businesses identified as victims in CPD data have been removed from this dataset.

    Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

    Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

    Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

  7. Prevalence rate of violent crime U.S. 2014-2022, by race/ethnicity

    • statista.com
    Updated Sep 14, 2023
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    Statista (2023). Prevalence rate of violent crime U.S. 2014-2022, by race/ethnicity [Dataset]. https://www.statista.com/statistics/424141/prevalence-rate-of-violent-crime-in-the-us-by-ethnicity/
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    Dataset updated
    Sep 14, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, the prevalence of violent crime increased for all races in the United States in comparison to the previous year. In that year, around **** percent of White Americans experienced one or more violent victimizations and approximately **** percent of Black or African American people were the victims of a violent crime.

  8. d

    COVID-19 Cases and Deaths by Race/Ethnicity - ARCHIVE

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Aug 12, 2023
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    data.ct.gov (2023). COVID-19 Cases and Deaths by Race/Ethnicity - ARCHIVE [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-and-deaths-by-race-ethnicity
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    Dataset updated
    Aug 12, 2023
    Dataset provided by
    data.ct.gov
    Description

    Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical

  9. Brazil: homicide rate 2006-2022, by ethnicity

    • statista.com
    Updated Oct 29, 2024
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    Statista (2024). Brazil: homicide rate 2006-2022, by ethnicity [Dataset]. https://www.statista.com/statistics/867757/homicide-rate-brazil-ethnicity/
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    Dataset updated
    Oct 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Brazil
    Description

    The homicide rate registered in Brazil impacts ethnicities very differently. Whereas the number of homicides per 100,000 black or brown people increased by 33 percent between 2006 and 2017, the homicide rate of non-black or brown individuals declined by nearly 19 percent in the same period. In 2022, the homicide rate for the black ethnic group decreased compared to the previous year.

  10. a

    Interactive Map of Atlanta Homicide Data (33N)

    • hub.arcgis.com
    • opendata.atlantaregional.com
    • +2more
    Updated Aug 13, 2018
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    Georgia Association of Regional Commissions (2018). Interactive Map of Atlanta Homicide Data (33N) [Dataset]. https://hub.arcgis.com/documents/2acbb8846d6e4457af81ca5d15796b76
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    Dataset updated
    Aug 13, 2018
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Atlanta
    Description

    This interactive mapping tool, created for the 33N blog, displays homicides in the City of Atlanta between January 2007 and February 2017 by race/ethnicity and sex of the victim. The data for this tool was provided by the Washington Post as part of an investigative project which compiled information on 54,000 homicides in the U.S. to identify hot spots where homicides rates are high but arrests are low.

  11. Uniform Crime Reporting Program Data: Hate Crime Data, 2011 [Record-Type...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
    + more versions
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    Bureau of Justice Statistics (2025). Uniform Crime Reporting Program Data: Hate Crime Data, 2011 [Record-Type Files] [Dataset]. https://catalog.data.gov/dataset/uniform-crime-reporting-program-data-hate-crime-data-2011-record-type-files-3be49
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Description

    In response to a growing concern about hate crimes, the United States Congress enacted the Hate Crime Statistics Act of 1990. The Act requires the attorney general to establish guidelines and collect, as part of the Uniform Crime Reporting (UCR) Program, data "about crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity, including where appropriate the crimes of murder and non-negligent manslaughter, forcible rape, aggravated assault, simple assault, intimidation, arson, and destruction, damage or vandalism of property." Hate crime data collection was required by the Act to begin in calendar year 1990 and to continue for four successive years. In September 1994, the Violent Crime Control and Law Enforcement Act amended the Hate Crime Statistics Act to add disabilities, both physical and mental, as factors that could be considered a basis for hate crimes. Although the Act originally mandated data collection for five years, the Church Arson Prevention Act of 1996 amended the collection duration "for each calendar year," making hate crime statistics a permanent addition to the UCR program. As with the other UCR data, law enforcement agencies contribute reports either directly or through their state reporting programs. Information contained in the data includes number of victims and offenders involved in each hate crime incident, type of victims, bias motivation, offense type, and location type.

  12. Uniform Crime Reporting Program Data [United States]: Arrests by Age, Sex,...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
    + more versions
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    Bureau of Justice Statistics (2025). Uniform Crime Reporting Program Data [United States]: Arrests by Age, Sex, and Race, Summarized Yearly, 1992 [Dataset]. https://catalog.data.gov/dataset/uniform-crime-reporting-program-data-united-states-arrests-by-age-sex-and-race-summarized--4f801
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Area covered
    United States
    Description

    These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 43 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing, per reporting police agency: an agency header record, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to logical record length format with the agency header record variables copied onto the detail records. Consequently, each record contains arrest counts for a particular agency-offense.

  13. Number of workplace homicide victims U.S. 2019, by race and ethnicity

    • statista.com
    • ai-chatbox.pro
    Updated Dec 16, 2024
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    Statista (2024). Number of workplace homicide victims U.S. 2019, by race and ethnicity [Dataset]. https://www.statista.com/statistics/1346105/number-workplace-homicide-victims-us-race-ethnicity/
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    Dataset updated
    Dec 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United States
    Description

    In 2019, there were 454 victims of workplace homicide across the United States. Of these victims, 197 were white and 127 were Black. The remaining victims were predominantly Hispanic or Latino.

  14. Race and the criminal justice system statistics 2018

    • gov.uk
    Updated Nov 28, 2019
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    Ministry of Justice (2019). Race and the criminal justice system statistics 2018 [Dataset]. https://www.gov.uk/government/statistics/race-and-the-criminal-justice-system-statistics-2018
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    Dataset updated
    Nov 28, 2019
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    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.

    Introduction

    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.

    Key findings

    Victims

    • The Asian ethnic group had the lowest proportion of both adults (2%) and children (5%) who had experienced personal crime in the last year. In 2018/19, both adults and children from the Asian ethnic group were half as likely to report victimisation when compared to the White ethnic group.
    • A higher proportion of Black homicides were against children, 17% of Black victims were 17 or younger, compared to an average of 11% across all ethnicities. Between 2015/16 and 2017/18, Black children made up 20% of all child victims, while Black victims made up 13% of victims across all age groups.

    Police Activity

    • The proportion of stop and searches conducted on White suspects decreased from 75% in 2014/15 to 59% in 2018/19 and increased for all minority ethnic groups. The largest increases were from 13% to 22% for Black suspects and from 8% to 13% for Asian suspects.
    • In the last five years, the proportion of stop and searches involving Black suspects in London increased from 30% to 37%, now equal to the number of White suspects searched. In 2018/19, 48% of all stop and searches (where ethnicity is known) were conducted in London, and increasingly involving a higher proportion of suspects from minority ethnic groups when compared to the rest of England and Wales.
    • Black suspects had the highest proportion of arrests that resulted from stop and searches in the latest year, at 20% which has increased from 15% since 2014/15. This is driven by a higher number of stop and searches in London, where resultant arrests accounted for 22% of all arrests, compared to 5% for the rest of England and Wales. For other groups, between 6% and 13% of arrests resulted from stop and searches.
    • In 2018/19, two thirds (67%) of children arrested in London were from minority ethnic groups, compared to 21% of children arrested in the rest of England and Wales. Just over half (52%) of adults arrested in London were from minority ethnic groups, compared to 22% of adults arrested in the rest of England and Wales.

    Defendants

    • In the latest year, the largest fall in the volume of prosecutions and convictions for indictable offences was seen in the Asian group, down by 22% and 20% respectively. Prosecutions and convictions fell by 18% and 16% for Black defendants, by 13% each for White defendants, by 8% and 10% for defendants from Mixed ethnic groups and by 7% and 14% for defendants from Chinese or Other ethnic groups.
    • White defendants consistently had the highest conviction ratio for indictable offences over the last 5 years (with the exception of 2015) and was 85% in 2018. The conviction ratios for White, Asian (83%) and Black (81%) defendants have converged with each other over the last 5 years, remained constant for defendants from Mixed ethnic groups (77%) and fallen for Chinese or Other ethnic groups (75%).
    • Compared to White defendants (38%), larger proportions of Asian (40%), Mixed ethnicity (45%), Black (46%) and Chinese or Other (46%) defendants were remanded in custody for indictable

  15. Brazil: number of homicides 2006-2022, by ethnicity

    • statista.com
    Updated Oct 29, 2024
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    Statista (2024). Brazil: number of homicides 2006-2022, by ethnicity [Dataset]. https://www.statista.com/statistics/867730/number-homicides-brazil-ethnicity/
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    Dataset updated
    Oct 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Brazil
    Description

    The number of black and Pardo Brazilian people murdered in Brazil had been increasing throughout the years up until 2017. In 2022, around 35,500 black and Pardo citizens were killed in the South American country, down from almost 37,000 recorded one year before.

  16. Data from: Study of Race, Crime, and Social Policy in Oakland, California,...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Study of Race, Crime, and Social Policy in Oakland, California, 1976-1982 [Dataset]. https://catalog.data.gov/dataset/study-of-race-crime-and-social-policy-in-oakland-california-1976-1982-b8cd2
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    Oakland, California
    Description

    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.

  17. Uniform Crime Reporting Program Data: Arrests by Age, Sex, and Race, United...

    • icpsr.umich.edu
    ascii, delimited, r +3
    Updated Jul 29, 2024
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    United States. Federal Bureau of Investigation (2024). Uniform Crime Reporting Program Data: Arrests by Age, Sex, and Race, United States, 2022 [Dataset]. http://doi.org/10.3886/ICPSR39062.v1
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    stata, delimited, r, sas, ascii, spssAvailable download formats
    Dataset updated
    Jul 29, 2024
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Federal Bureau of Investigation
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/39062/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/39062/terms

    Time period covered
    2022
    Area covered
    United States
    Description

    These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 44 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

  18. c

    CMPD Violent Crime Attribute

    • data.charlottenc.gov
    Updated Mar 18, 2024
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    City of Charlotte (2024). CMPD Violent Crime Attribute [Dataset]. https://data.charlottenc.gov/datasets/charlotte::cmpd-violent-crime-attribute-1/about
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    Dataset updated
    Mar 18, 2024
    Dataset authored and provided by
    City of Charlotte
    Area covered
    Description

    Attributes/demographics of FBI Uniform Crime Reporting Part I violent crime victims and offenders, updated monthly, aggregated to the CMPD jurisdiction, Neighborhood Profile Area (NPA), and Violent Crime Hotspot (focus areas for the City's violence reduction initiative). Monthly counts cover the time frame Jan-2015 to present. Crime categories comprising violent crime include homicide, rape, robbery, and aggravated assault. Attributes of violent crime victims include counts of domestic violence (DV and Non-DV), age group, gender, and race/ethnicity. Attributes of violent crime offenders include counts of age group, gender, and race/ethnicity.

  19. Gun homicide rate U.S. 2022, by race and age

    • ai-chatbox.pro
    • statista.com
    Updated Feb 6, 2025
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    Statista (2025). Gun homicide rate U.S. 2022, by race and age [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstatistics%2F1466060%2Fgun-homicide-rate-by-race-and-age-us%2F%23XgboD02vawLbpWJjSPEePEUG%2FVFd%2Bik%3D
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    In the United States, Black people have higher rates of gun homicide than White people across all age groups. As of 2022, gun homicide rates were highest among Black people aged between 15 and 24 years, at 63.78 gun homicides per 100,000 of the population. In comparison, there were only 2.58 gun homicides per 100,000 of the White population within this age range. However, the risk for gun homicide was greatest among all adolescents and adults between the ages of 15 to 44 in that year. The impact of guns on young Americans In the last few years, firearms have become the leading cause of death for American children and teenagers aged one to 19 years old, accounting for more deaths than car crashes and diseases. School shootings also remain on the rise recently, with the U.S. recording 57 times as many school shootings than other high-income nations from 2009 to 2018. Black students in particular experience a disproportionately high number of school shootings relative to their population, and K-12 teachers at schools made up mostly of students of color are more likely to report feeling afraid that they or their students would be a victim of attack or harm. The right to bear arms Despite increasingly high rates of gun-related violence, gun ownership remains a significant part of American culture, largely due to the fact that the right to bear arms is written into the U.S. Constitution. Although firearms are the most common murder weapon used in the U.S., accounting for approximately 15,000 homicides in 2022, almost half of American households have at least one firearm in their possession. Consequently, it is evident that firearms remain easily accessible nationwide, even though gun laws may vary from state to state. However, the topic of gun control still causes political controversy, as the majority of Republicans agree that it is more important to protect the right of Americans to own guns, while Democrats are more inclined to believe that it is more important to limit gun ownership.

  20. d

    Data from: Homicides in New York City, 1797-1999 [And Various Historical...

    • datasets.ai
    • icpsr.umich.edu
    • +1more
    0
    + more versions
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    Department of Justice, Homicides in New York City, 1797-1999 [And Various Historical Comparison Sites] [Dataset]. https://datasets.ai/datasets/homicides-in-new-york-city-1797-1999-and-various-historical-comparison-sites-f1e29
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    0Available download formats
    Dataset authored and provided by
    Department of Justice
    Area covered
    New York
    Description

    There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series on homicides per capita for New York City that spans two centuries. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. Data were also gathered on various other sites, particularly in England, to allow for comparisons on important issues, such as the post-World War II wave of violence. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. The annual count data (Parts 1 and 3) were derived from multiple sources, including the Federal Bureau of Investigation's Uniform Crime Reports and Supplementary Homicide Reports, as well as other official counts from the New York City Police Department and the City Inspector in the early 19th century. The data include a combined count of murder and manslaughter because charge bargaining often blurs this legal distinction. The individual-level data (Part 2) were drawn from coroners' indictments held by the New York City Municipal Archives, and from daily newspapers. Duplication was avoided by keeping a record for each victim. The estimation technique known as "capture-recapture" was used to estimate homicides not listed in either source. Part 1 variables include counts of New York City homicides, arrests, and convictions, as well as the homicide rate, race or ethnicity and gender of victims, type of weapon used, and source of data. Part 2 includes the date of the murder, the age, sex, and race of the offender and victim, and whether the case led to an arrest, trial, conviction, execution, or pardon. Part 3 contains annual homicide counts and rates for various comparison sites including Liverpool, London, Kent, Canada, Baltimore, Los Angeles, Seattle, and San Francisco.

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Statista (2024). Number of murder offenders 2023, by race [Dataset]. https://www.statista.com/statistics/1466623/murder-offenders-in-the-us-by-race/
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Number of murder offenders 2023, by race

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Dataset updated
Nov 7, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

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.

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