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 2024.

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.

BackgroundGun violence has shortened the average life expectancy of Americans, and better knowledge about the root causes of gun violence is crucial to its prevention. While some empirical evidence exists regarding the impacts of social and economic factors on violence and firearm homicide rates, to the author’s knowledge, there has yet to be a comprehensive and comparative lagged, multilevel investigation of major social determinants of health in relation to firearm homicides and mass shootings.Methods and findingsThis study used negative binomial regression models and geolocated gun homicide incident data from January 1, 2015, to December 31, 2015, to explore and compare the independent associations of key state-, county-, and neighborhood-level social determinants of health—social mobility, social capital, income inequality, racial and economic segregation, and social spending—with neighborhood firearm-related homicides and mass shootings in the United States, accounting for relevant state firearm laws and a variety of state, county, and neighborhood (census tract [CT]) characteristics. Latitude and longitude coordinates on firearm-related deaths were previously collected by the Gun Violence Archive, and then linked by the British newspaper The Guardian to CTs according to 2010 Census geographies. The study population consisted of all 74,134 CTs as defined for the 2010 Census in the 48 states of the contiguous US. The final sample spanned 70,579 CTs, containing an estimated 314,247,908 individuals, or 98% of the total US population in 2015. The analyses were based on 13,060 firearm-related deaths in 2015, with 11,244 non-mass shootings taking place in 8,673 CTs and 141 mass shootings occurring in 138 CTs. For area-level social determinants, lag periods of 3 to 17 years were examined based on existing theory, empirical evidence, and data availability. County-level institutional social capital (levels of trust in institutions), social mobility, income inequality, and public welfare spending exhibited robust relationships with CT-level gun homicide rates and the total numbers of combined non-mass and mass shooting homicide incidents and non-mass shooting homicide incidents alone. A 1–standard deviation (SD) increase in institutional social capital was linked to a 19% reduction in the homicide rate (incidence rate ratio [IRR] = 0.81, 95% CI 0.73–0.91, p < 0.001) and a 17% decrease in the number of firearm homicide incidents (IRR = 0.83, 95% CI 0.73–0.95, p = 0.01). Upward social mobility was related to a 25% reduction in the gun homicide rate (IRR = 0.75, 95% CI 0.66–0.86, p < 0.001) and a 24% decrease in the number of homicide incidents (IRR = 0.76, 95% CI 0.67–0.87, p < 0.001). Meanwhile, 1-SD increases in the neighborhood percentages of residents in poverty and males living alone were associated with 26%–27% and 12% higher homicide rates, respectively. Study limitations include possible residual confounding by factors at the individual/household level, and lack of disaggregation of gun homicide data by gender and race/ethnicity.ConclusionsThis study finds that the rich–poor gap, level of citizens’ trust in institutions, economic opportunity, and public welfare spending are all related to firearm homicide rates in the US. Further establishing the causal nature of these associations and modifying these social determinants may help to address the growing gun violence epidemic and reverse recent life expectancy declines among Americans.

This dataset provides highly detailed (Block Level) views of various demographics for Manhattan, New York city. this dataset includes information on age, race, sex, income, housing, and various other attributes. This data comes from the 2000 Us Census and was joined to the Census Tiger line files to create the output. enjoy!

We used individual-level death data to estimate county-level life expectancy at 25 (e25) for Whites, Black, AIAN and Asian in the contiguous US for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. Individual death data from the National Center for Health Statistics were aggregated as death counts into five-year age groups by county and race-sex groups for the contiguous US for years 2000-2005 (National Center for Health Statistics 2000-2005). We used bridged-race population estimates to calculate five-year mortality rates. The bridged population data mapped 31 race categories, as specified in the 1997 Office of Management and Budget standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (the same as race categories in mortality registration) (Ingram et al. 2003). The urban-rural gradient was represented by the 2003 Rural Urban Continuum Codes (RUCC), which distinguished metropolitan counties by population size, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area (United States Department of Agriculture 2016). We obtained county-level sociodemographic data for 2000-2005 from the US Census Bureau. These included median household income, percent of population attaining greater than high school education (high school%), and percent of county occupied rental units (rent%). We obtained county violent crime from Uniform Crime Reports and used it to calculate mean number of violent crimes per capita (Federal Bureau of Investigation 2010). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Request to author. Format: Data are stored as csv files. This dataset is associated with the following publication: Jian, Y., L. Neas, L. Messer, C. Gray, J. Jagai, K. Rappazzo, and D. Lobdell. Divergent trends in life expectancy across the rural-urban gradient among races in the contiguous United States. International Journal of Public Health. Springer Basel AG, Basel, SWITZERLAND, 64(9): 1367-1374, (2019).

These data assess the effects of the risk of local jail incarceration and of police aggressiveness in patrol style on rates of violent offending. The collection includes arrest rates for public order offenses, size of county jail populations, and numbers of new prison admissions as they relate to arrest rates for index (serious) crimes. Data were collected from seven sources for each city. CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: SUMMARY TAPE FILE 1A (ICPSR 7941), provided county-level data on number of persons by race, age, and age by race, number of persons in households, and types of households within each county. CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: SUMMARY TAPE FILE 3A (ICPSR 8071), measured at the city level, provided data on total population, race, age, marital status by sex, persons in household, number of households, housing, children, and families above and below the poverty level by race, employment by race, and income by race within each city. The Federal Bureau of Investigation (FBI) 1980 data provided variables on total offenses and offense rates per 100,000 persons for homicides, rapes, robbery, aggravated assault, burglary, larceny, motor vehicle offenses, and arson. Data from the FBI for 1980-1982, averaged per 100,000, provided variables for the above offenses by sex, age, and race, and the Uniform Crime Report arrest rates for index crimes within each city. The NATIONAL JAIL CENSUS for 1978 and 1983 (ICPSR 7737 and ICPSR 8203), aggregated to the county level, provided variables on jail capacity, number of inmates being held by sex, race, and status of inmate's case (awaiting trial, awaiting sentence, serving sentence, and technical violations), average daily jail populations, number of staff by full-time and part-time, number of volunteers, and number of correctional officers. The JUVENILE DETENTION AND CORRECTIONAL FACILITY CENSUS for 1979 and 1982-1983 (ICPSR 7846 and 8205), aggregated to the county level, provided data on the number of individuals being held by type of crime and sex, as well as age of juvenile offenders by sex, average daily prison population, and payroll and other expenditures for the institutions.

This dataset was created from the CDC's National Vital Statistics Reports Volume 56, Number 6. The dataset includes all data available from this report by state level and includes births by race and Hispanic origin, births to unmarried women, rates of cesarean delivery, and twin and multiple birth rates. The data are final for 2005. No value is represented by a -1. "Descriptive tabulations of data reported on the birth certificates of the 4.1 million births that occurred in 2005 are presented. Denominators for population-based rates are postcensal estimates derived from the U.S. 2000 census".

The National Crime Victimization Survey (NCVS) Series, previously called the National Crime Surveys (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. The survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual attack, 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 version of the NCVS, referred to as the collection year, contains records from interviews conducted in the 12 months of the given year.

This research project examined rural and urban trends in family and intimate partner homicide for the 20-year period from 1980 through 1999. The construct of place served as a backdrop against which changes in trends in family/partner homicide were tracked, and against which various independent measures that purportedly explain variation in the rates were tested. The project merged data from several sources. The offender data file from the Federal Bureau of Investigation's (FBI) Supplementary Homicide Report (SHR) series for 1980 through 1999 was the primary data source. Data for arrests for violent crime, drug, and alcohol-related offenses were obtained from the FBI Report A Arrest File. Population, population density, and race (and racial segregation) data from the decennial U.S. Census for 1980, 1990, and 2000 were also obtained. Data on hospitals, educational attainment, unemployment, and per capita income were obtained from the 2002 Area Resource File (ARF). The total number of proprietors (farm and non-farm) in the United States by state and county for each year were provided by the Regional Economic Profiles data. The project's population and proximity indicator used four categories: metropolitan, nonmetropolitan populations adjacent to a metropolitan area, nonmetropolitan populations not adjacent to a metropolitan area, and rural. Data include homicide rates for 1980 through 1999 for intimate partner homicide, family homicide, all other homicide, and all homicide. Additional variables are included as measures of community socioeconomic distress, such as residential overcrowding, isolation, traditionalist views of women and family, lack of access to health care, and substance abuse. Five-year averages are included for each of the rates and measures listed above.

These data were collected to examine the relationships among crime rates, residents' attitudes, physical deterioration, and neighborhood structure in selected urban Baltimore neighborhoods. The data collection provides both block- and individual-level neighborhood data for two time periods, 1981-1982 and 1994. The block-level files (Parts 1-6) include information about physical conditions, land use, people counts, and crime rates. Parts 1-3, the block assessment files, contain researchers' observations of street layout, traffic, housing type, and general upkeep of the neighborhoods. Part 1, Block Assessments, 1981 and 1994, contains the researchers' observations of sampled blocks in 1981, plus selected variables from Part 3 that correspond to items observed in 1981. Nonsampled blocks (in Part 2) are areas where block assessments were done, but no interviews were conducted. The "people counts" file (Part 4) is an actual count of people seen by the researchers on the sampled blocks in 1994. Variables for this file include the number, gender, and approximate age of the people seen and the types of activities they were engaged in during the assessment. Part 5, Land Use Inventory for Sampled Blocks, 1994, is composed of variables describing the types of buildings in the neighborhood and their physical condition. Part 6, Crime Rates and Census Data for All Baltimore Neighborhoods, 1970-1992, includes crime rates from the Baltimore Police Department for aggravated assault, burglary, homicide, larceny, auto theft, rape, and robbery for 1970-1992, and census information from the 1970, 1980, and 1990 United States Censuses on the composition of the housing units and the age, gender, race, education, employment, and income of residents. The individual-level files (Parts 7-9) contain data from interviews with neighborhood leaders, as well as telephone surveys of residents. Part 7, Interviews with Neighborhood Leaders, 1994, includes assessments of the level of involvement in the community by the organization to which the leader belongs and the types of activities sponsored by the organization. The 1982 and 1994 surveys of residents (Parts 8 and 9) asked respondents about different aspects of their neighborhoods, such as physical appearance, problems, and crime and safety issues, as well as the respondents' level of satisfaction with and involvement in their neighborhoods. Demographic information on respondents, such as household size, length of residence, marital status, income, gender, and race, is also provided in this file.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study examined maternal and youth self-reports of arrests and convictions with official records of crime among participants in three randomized controlled trials of the Nurse-Family Partnership (NFP) in Denver, Colorado, Elmira, New York, and Memphis, Tennessee. Official records were obtained from third-party sources as well as directly from New York State Division of Criminal Justice Services. The collection contains 10 SAS data files: dmom_all.sas7bdat (n=735; 3 variables) dmom_control.sas7bdat (n=247; 26 variables) echild_all.sas7bdat (n=374; 4 variables) echild_control.sas7bdat (n=173; 22 variables) emom_all.sas7bdat (n=399; 4 variables) emom_control.sas7bdat (n=184; 17 variables) mchild_all.sas7bdat (n=708; 5 variables) mchild_control.sas7bdat (n=482; 46 variables) mmom_all.sas7bdat (n=742; 5 variables) mmom_control.sas7bdat (n=514; 25 variables) Demographic variables include race, ethnicity, highest grade completed, household income, marital status, housing density, maternal age, maternal education, husband/boyfriend education, and head of household employment status.

This dataset includes Table 11 of the Maryland Vital Statistics Annual Report 2005 which includes GENERAL FERTILITY RATES (Total births per 1,000 women ages 15-44.) AND BIRTH RATES (Live births per 1,000 women in specified age group.) BY AGE OF MOTHER, RACE OF MOTHER, REGION, AND POLITICAL SUBDIVISION, MARYLAND, 2005. Rates that are based on fewer than five events in the numerator are not presented and are represented here as -1. Numbers and rates for Baltimore city and Baltimore county are combined.

HAZUS is an abbreviation for Hazards United States, and was developed by FEMA. The HAZUS dataset was designed to estimate the potential physical, economic and social losses during hazardous events such as flooding or earthquakes. To measure the social impact of these events, HAZUS includes detailed demographic data for the United States. This dataset pulls out the racial data from the demographic files, at the census block level for the Washington portion of the Portland Metropolitan Statistic Area (MSA). Attributes include Whites, Blacks, Asians, Hispanics, Hawaiian and Pacific Islanders, Native Americans, and populations stating other race. Demographics data was recent as of May 2006.

This dataset was retrieved from the U.S. Department of Justice Federal Bureau of Investigation Criminal Justice Information Services Division website on February 29, 2008. "This table provides the estimated number of offenses and the actual number of offenses reported in the Metropolitan Statistical Areas (MSA), cities outside metropolitan areas, and nonmetropolitan counties, and the rate (per 100,000 inhabitants) for each grouping, and the estimated population for each state" however to simplify the dataset, I only included the state total and the rate for each state. Data for Puerto Rico was not included. "The FBI collects these data through the Uniform Crime Reporting (UCR) Program". Please see the Data Declaration for further information on the data set. Values of -1 represent no value.

The aim of this data collection was to gauge the impact of legalized casino gambling on the level and spatial distribution of crime in the Atlantic City region by comparing crime rates before and after the introduction of this type of gambling in the area. Data for the years 1972 through 1984 were collected from various New Jersey state publications for 64 localities and include information on population size and density, population characteristics of race, age, per capita income, education and home ownership, real estate values, number of police employees and police expenditures, total city expenditure, and number of burglaries, larcenies, robberies and vehicle thefts. Spatial variables include population attributes standardized by land area in square miles, and measures of accessibility, location, and distance from Atlantic City. For the 1970/1980 data file, additional variables pertaining to population characteristics were created from census data to match economic and crime attributes found in the 1972-1984 data. Data on eight additional locations are available in the 1970/1980 file.

This dataset is a boundary file obtained from the US Census Tiger Shape file library which can be found online. I downloaded the File for California then Used ESRI ArcMap to cut out the San Francisco MSA from Californai. Census demographic data was joined to the boundaries. This file includes attributes on Race and Populations and other demographic data.

This dataset shows the origin and race of residents. The data is part of the Census Transportation Planning Package (CTPP), and is the result of a cooperative effort between various groups including the State Departments of Transportation, U.S. Census Bureau, and the Federal Highway Administration. The data is a special tabulation of responses from households completing the decennial census long form. The data was collected in 2000 and is shown at tract level. This data can be found at http://www.transtats.bts.gov/Fields.asp?Table_ID=1341.

This dataset was found online at the Association of Religious Data Archives (ARDA) website. http://www.thearda.com/ . This data set shows information on religous groups throughout the United States. All data was uploaded as a polypoint centroids per county in the United States, in shapefile format. This Data set shows the Total congregations, Total Adherents, and Rate of Adherence per 1000 population for All religions in the United States and for the Mainline Religions.

This dataset has been migrated from our Geocommons platform, and lacks a description from the original posting user. This is not a Fortiusone provided dataset. Please keep this in mind, and make of the dataset what you will. Thank you for visiting Finder!

HAZUS is an abbreviation for Hazards United States, and was developed by FEMA. The HAZUS dataset was designed to estimate the potential physical, economic and social losses during hazardous events such as flooding or earthquakes. To measure the social impact of these events, HAZUS includes detailed demographic data for the United States. This dataset pulls out the income range data from the demographic files, at the census block level for the Kentucky section of the Cincinnati, Ohio Metropolitan Statistic Area (MSA). Income attributes include; incomes under $10k, incomes from $10k-$20k, $20k-$30k, and so on up until income of $100k+. Demographics data was recent as of May 2006.