This study was undertaken to obtain information on the characteristics of gun ownership, gun-carrying practices, and weapons-related incidents in the United States -- specifically, gun use and other weapons used in self-defense against humans and animals. Data were gathered using a national random-digit-dial telephone survey. The respondents were comprised of 1,905 randomly-selected adults aged 18 and older living in the 50 United States. All interviews were completed between May 28 and July 2, 1996. The sample was designed to be a representative sample of households, not of individuals, so researchers did not interview more than one adult from each household. To start the interview, six qualifying questions were asked, dealing with (1) gun ownership, (2) gun-carrying practices, (3) gun display against the respondent, (4) gun use in self-defense against animals, (5) gun use in self-defense against people, and (6) other weapons used in self-defense. A "yes" response to a qualifying question led to a series of additional questions on the same topic as the qualifying question. Part 1, Survey Data, contains the coded data obtained during the interviews, and Part 2, Open-Ended-Verbatim Responses, consists of the answers to open-ended questions provided by the respondents. Information collected for Part 1 covers how many firearms were owned by household members, types of firearms owned (handguns, revolvers, pistols, fully automatic weapons, and assault weapons), whether the respondent personally owned a gun, reasons for owning a gun, type of gun carried, whether the gun was ever kept loaded, kept concealed, used for personal protection, or used for work, and whether the respondent had a permit to carry the gun. Additional questions focused on incidents in which a gun was displayed in a hostile manner against the respondent, including the number of times such an incident took place, the location of the event in which the gun was displayed against the respondent, whether the police were contacted, whether the individual displaying the gun was known to the respondent, whether the incident was a burglary, robbery, or other planned assault, and the number of shots fired during the incident. Variables concerning gun use by the respondent in self-defense against an animal include the number of times the respondent used a gun in this manner and whether the respondent was hunting at the time of the incident. Other variables in Part 1 deal with gun use in self-defense against people, such as the location of the event, if the other individual knew the respondent had a gun, the type of gun used, any injuries to the respondent or to the individual that required medical attention or hospitalization, whether the incident was reported to the police, whether there were any arrests, whether other weapons were used in self-defense, the type of other weapon used, location of the incident in which the other weapon was used, and whether the respondent was working as a police officer or security guard or was in the military at the time of the event. Demographic variables in Part 1 include the gender, race, age, household income, and type of community (city, suburb, or rural) in which the respondent lived. Open-ended questions asked during the interview comprise the variables in Part 2. Responses include descriptions of where the respondent was when he or she displayed a gun (in self-defense or otherwise), specific reasons why the respondent displayed a gun, how the other individual reacted when the respondent displayed the gun, how the individual knew the respondent had a gun, whether the police were contacted for specific self-defense events, and if not, why not.

The share of American households owning at least one firearm has remained relatively steady since 1972, hovering between ** percent and ** percent. In 2023, about ** percent of U.S. households had at least one gun in their possession. Additional information on firearms in the United States Firearms command a higher degree of cultural significance in the United States than any other country in the world. Since the inclusion of the right to bear arms in the Second Amendment to the Constitution of the United States, firearms have held symbolic power beyond their already obvious material power. Despite many Americans being proud gun-owners, a large movement exists within the country in opposition to the freedom afforded to those in possession of these potentially deadly weapons. Those opposed to current gun regulation have sourced their anger from the large number of deaths due to firearms in the country, as well as the high frequency of gun violence apparent in comparison to other developed countries. Furthermore, the United States has fallen victim to a number of mass shootings in the last two decades, most of which have raised questions over the ease at which a person can obtain a firearm. Although this movement holds a significant position in the public political discourse of the United States, meaningful change regarding the legislation dictating the ownership of firearms has not occurred. Critics have pointed to the influence possessed by the National Rifle Association through their lobbying of public officials. The National Rifle Association also lobbies for the interests of firearm manufacturing in the United States, which has continued to rise since a fall in the early 2000s.

In the United States, gun laws vary from one state to the next; whether residents need a permit or a background check to purchase a firearm, whether residents must undergo firearm training before making this purchase, and whether residents can openly carry their guns in public is dependent upon state legislation. As of 2024, ** U.S. states required background checks and/or permits for the purchase of a handgun. A further ** states had regulations on openly carrying firearms in public, however, only California, Connecticut, Florida, and Illinois had completely prohibited open carry for all firearms. In comparison, Maryland, New Jersey, and New York prohibited open carry for handguns but either did not have regulations in place or required a permit for other types of guns. A constitutional right The Second Amendment of the Constitution, which states that citizens have the right to bear arms, has made it difficult for any gun control legislation to be passed on a national level in the United States. As a result, gun control laws in the U.S. are state-based, and often differ based on political perspectives. States with strong gun laws in place, such as Massachusetts, generally experience less gun violence, however, some states with strong gun laws, such as Maryland, continue to face high rates of gun violence, which has largely been attributed to gun trafficking activity found throughout the nation. A culture of gun owners In comparison to other high-income countries with stricter gun control laws, the United States has the highest gun homicide rate at **** gun homicides per 100,000 residents. However, despite increasing evidence that easy access to firearms, whether legal or illegal, encourages higher rates of gun violence, the United States continues to foster an environment in which owning a firearm is seen as personal freedom. Almost **** of U.S. households have reported owning at least one firearm and ** percent of registered voters in the U.S. were found to believe that it was more important to protect the right of Americans to own guns, compared to ** percent who said it was more important to limit gun ownership.

Firearms background checks for the USA for 2012 (Jan-Nov) and since 1999.These statistics represent the number of firearm background checks initiated through the NICS. They do not represent the number of firearms sold. NICS is used by Federal Firearms Licensees (FFLs) to instantly determine whether a prospective buyer is eligible to buy firearms or explosives. Before ringing up the sale, cashiers call in a check to the FBI or to other designated agencies to ensure that each customer does not have a criminal record or isn't otherwise ineligible to make a purchase. More than 100 million such checks have been made in the last decade, leading to more than 700,000 denials. More information on NICS - http://www.fbi.gov/about-us/cjis/nics Some really useful informations such as the rate of checks per 1000 people. All data is provided by state. Downloaded from the Guardian Datablog - http://www.guardian.co.uk/news/datablog/2012/dec/17/how-many-guns-us and then joined to USA States data http://geocommons.com/overlays/21424. Gun data originally from FBI http://www.fbi.gov/about-us/cjis/nics. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-12-17 and migrated to Edinburgh DataShare on 2017-02-21.

THIS DATASET WAS LAST UPDATED AT 2:10 AM EASTERN ON JUNE 29

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

Number and percentage of homicide victims, by type of firearm used to commit the homicide (total firearms; handgun; rifle or shotgun; fully automatic firearm; sawed-off rifle or shotgun; firearm-like weapons; other firearms, type unknown), Canada, 1974 to 2018.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Gun Plain township. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Gun Plain township. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in Gun Plain township, the median household income stands at $123,379 for householders within the 25 to 44 years age group, followed by $98,079 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $42,301.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Plain township median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Gun Barrel City. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Gun Barrel City. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in Gun Barrel City, the median household income stands at $81,849 for householders within the 45 to 64 years age group, followed by $66,847 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $64,527.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Barrel City median household income by age. You can refer the same here

The data on mass shootings is from https://www.gunviolencearchive.org/ . This dataset on mass shootings for the period 2014-2023 was provided on Feb 19, 2024 by the Data Manager (Ms. Sharon Williams) at the Gun Violence Archive (https://www.gunviolencearchive.org/) on a data request. Minimal curation was done on this data – the date variable was split into year, month and day. See the codebook for full details.A mass shooting is defined as four or more people injured or killed, because of firearms, excluding the shooter.The curated datasets are included here along with a research question and guiding questions.For information of how this data is collected, go to: https://www.gunviolencearchive.org/explainerDefinition for mass shooting and mass murder from the above website is given verbatim below:Mass Shooting Methodology and Reasoning: Mass Shootings are, for the most part an American phenomenon. While they are generally grouped together as one type of incident they are several different types including public shootings, bar/club incidents, family annihilations, drive-by, workplace and those which defy description but with the established foundation definition being that they have a minimum of four victims shot, either injured or killed, not including any shooter who may also have been killed or injured in the incident. GVA also presents the count of Mass Murder which, like the FBI's definition is four or more victims, killed, not including the shooter. Mass Murder by gun is a subset of the Mass Shooting count.

The United States is ranked first in gun possession globally and is among the countries suffering the most from firearm violence. Several aspects of the US firearm ecosystem have been detailed over the years, mostly focusing on nation- or state-level phenomena. Systematic, high-resolution studies that compare US cities are largely lacking, leaving several questions open. For example, how does firearm violence vary with the population size of a US city? Are guns more prevalent and accessible in larger cities? In search of answers to these questions, we apply urban scaling theory, which has been instrumental in understanding the present and future of urbanization for the past 15 years. We collate a dataset about firearm violence, accessibility and ownership in 929 cities, ranging from 10,000 to 20,000,000 people. We discover superlinear scaling of firearm violence (measured through the incidence of firearm homicides and armed robberies) and sublinear scaling of both firearm ownership (inferred from the percentage of suicides that are committed with firearm) and firearm accessibility (measured as the prevalence of federal firearm-selling licenses). To investigate the mechanism underlying the US firearm ecosystem, we establish a novel information-theoretic methodology that infers associations from the variance of urban features about scaling laws. We unveil influence of violence and firearm accessibility on firearm ownership, which we model through a Cobb–Douglas function. Such an influence suggests that self-protection could be a critical driver of firearm ownership in US cities, whose extent is moderated by access to firearms.

The Concealed Carry Weapons License Database (CCWLD) is a longitudinal collection of state and county-level data on concealed carry weapons licenses (CCWs). Data were collected from a series of internet searches and freedom of information requests sent to state governments during the fall of 2019 and winter of 2020. Data cleaning was conducted by research assistants and by Trent Steidley in the winter of 2021.Documentation memos for each state are provided in the archived files. Along with raw data files, Stata syntax for cleaning, and the final cleaned database.This database was supported with funding from the Center on American Politics at the University of Denver and a Professional Research Opportunity for Faculty (PROF) grant from the University of Denver. If you use these data in your research please cite them appropriately.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Gun Barrel City, TX, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Gun Barrel City, TX reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Gun Barrel City households based on income levels.

Key observations

• For Family Households: In Gun Barrel City, the majority of family households, representing 19.23%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 1.33%, have incomes falling $100,000 to $124,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Gun Barrel City, the majority of non-family households, accounting for 19.15%, have income $60,000 to $74,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $100,000 to $124,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Gun Barrel City, TX (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Gun Barrel City, TX
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Gun Barrel City, TX
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Gun Barrel City, TX

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Barrel City median household income. You can refer the same here

Weapons Sales in the United States decreased to 11287 SIPRI TIV Million in 2023 from 15592 SIPRI TIV Million in 2022. United States Weapons Sales - values, historical data, forecasts and news - updated on July of 2025.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Gun Plain Township, Michigan, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Gun Plain Township, Michigan reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Gun Plain township households based on income levels.

Key observations

• For Family Households: In Gun Plain township, the majority of family households, representing 19.44%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $10,000 to $14,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Gun Plain township, the majority of non-family households, accounting for 26.4%, have income $25,000 to $29,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $10,000 to $14,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Gun Plain Township, Michigan (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Gun Plain Township, Michigan
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Gun Plain Township, Michigan
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Gun Plain Township, Michigan

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Plain township median household income. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Gun Plain township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Gun Plain township, the median income for all workers aged 15 years and older, regardless of work hours, was $53,731 for males and $29,536 for females.

These income figures highlight a substantial gender-based income gap in Gun Plain township. Women, regardless of work hours, earn 55 cents for each dollar earned by men. This significant gender pay gap, approximately 45%, underscores concerning gender-based income inequality in the township of Gun Plain township.

- Full-time workers, aged 15 years and older: In Gun Plain township, among full-time, year-round workers aged 15 years and older, males earned a median income of $69,698, while females earned $61,513, resulting in a 12% gender pay gap among full-time workers. This illustrates that women earn 88 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the township of Gun Plain township.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Gun Plain township.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Plain township median household income by race. You can refer the same here

description: This set of raw data contains information from Bloomington Police Department cases, specifically it identified cases where officers have fired a gun at a suspect. **Please note that this particular dataset contains no data. As of current date, the Bloomington Police Department has had no officer involved shootings to report. ** # Key code for Race: - A- Asian/Pacific Island, Non-Hispanic - B- African American, Non-Hispanic - I- Indian/Alaskan Native, Non-Hispanic - K- African American, Hispanic - L- Caucasian, Hispanic - N- Indian/Alaskan Native, Hispanic - P- Asian/Pacific Island, Hispanic - U- Unknown - W- Caucasian, Non-Hispanic # Key Code for Reading Districts: Example: LB519 - L for Law call or incident - B stands for Bloomington - 5 is the district or beat where incident occurred - All numbers following represents a grid sector. A map of the five districts can be located on Raidsonline.com, under the tab labeled Agency Layers. Disclaimer: The Bloomington Police Department takes great effort in making all sets of data as accurate as possible, but there is no avoiding the introduction of errors in this process. Information contained in this dataset may change over a period of time. The Bloomington Police Department is not responsible for any error or omission from this data or for the use, or interpretation of the results of any research conducted.; abstract: This set of raw data contains information from Bloomington Police Department cases, specifically it identified cases where officers have fired a gun at a suspect. **Please note that this particular dataset contains no data. As of current date, the Bloomington Police Department has had no officer involved shootings to report. ** # Key code for Race: - A- Asian/Pacific Island, Non-Hispanic - B- African American, Non-Hispanic - I- Indian/Alaskan Native, Non-Hispanic - K- African American, Hispanic - L- Caucasian, Hispanic - N- Indian/Alaskan Native, Hispanic - P- Asian/Pacific Island, Hispanic - U- Unknown - W- Caucasian, Non-Hispanic # Key Code for Reading Districts: Example: LB519 - L for Law call or incident - B stands for Bloomington - 5 is the district or beat where incident occurred - All numbers following represents a grid sector. A map of the five districts can be located on Raidsonline.com, under the tab labeled Agency Layers. Disclaimer: The Bloomington Police Department takes great effort in making all sets of data as accurate as possible, but there is no avoiding the introduction of errors in this process. Information contained in this dataset may change over a period of time. The Bloomington Police Department is not responsible for any error or omission from this data or for the use, or interpretation of the results of any research conducted.

Disclaimer: This list is updated monthly on the website. If up-to-the-minute accuracy is needed, contact us at 312-603-6328. This dataset contains businesses registered for Firearm Retailers.

Analysis of ‘Officer Involved Shootings’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/102a81cc-5f15-40da-ad02-edd606e9eb44 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Bloomington Police Department cases where officers have fired a gun at an individual.

Key code for Race:

A- Asian/Pacific Island, Non-Hispanic B- African American, Non-Hispanic C- Hawaiian/Other Pacific Island, Hispanic H- Hawaiian/Other Pacific Island, Non-Hispanic I- Indian/Alaskan Native, Non-Hispanic K- African American, Hispanic L- Caucasian, Hispanic N- Indian/Alaskan Native, Hispanic P- Asian/Pacific Island, Hispanic S- Asian, Non-Hispanic T- Asian, Hispanic U- Unknown W- Caucasian, Non-Hispanic

Key Code for Reading Districts:

Example: LB519

L for Law call or incident B stands for Bloomington 5 is the district or beat where incident occurred All numbers following represents a grid sector.

Disclaimer: The Bloomington Police Department takes great effort in making open data as accurate as possible, but there is no avoiding the introduction of errors in this process, which relies on data provided by many people and that cannot always be verified. Information contained in this dataset may change over a period of time. The Bloomington Police Department is not responsible for any error or omission from this data, or for the use or interpretation of the results of any research conducted.

--- Original source retains full ownership of the source dataset ---

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Gun Barrel City. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Gun Barrel City, the median income for all workers aged 15 years and older, regardless of work hours, was $34,623 for males and $28,611 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 17% between the median incomes of males and females in Gun Barrel City. With women, regardless of work hours, earning 83 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Gun Barrel City.

- Full-time workers, aged 15 years and older: In Gun Barrel City, among full-time, year-round workers aged 15 years and older, males earned a median income of $67,545, while females earned $51,190, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Gun Barrel City, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Barrel City median household income by race. You can refer the same here

The Washington Post spent a year determining how many children have been affected by school shootings, beyond just those killed or injured. To do that, reporters attempted to identify every act of gunfire at a primary or secondary school during school hours since the Columbine High massacre on April 20, 1999. Using Nexis, news articles, open-source databases, law enforcement reports, information from school websites, and calls to schools and police departments, The Post reviewed more than 1,000 alleged incidents, but counted only those that happened on campuses immediately before, during or just after classes. Shootings at after-hours events, accidental discharges that caused no injuries to anyone other than the person handling the gun, and suicides that occurred privately or posed no threat to other children were excluded. Gunfire at colleges and universities, which affects young adults rather than kids, also was not counted. After finding more than 200 incidents of gun violence that met The Post’s criteria, reporters organized them in a database for analysis. Because the federal government does not track school shootings, it’s possible that the database does not contain every incident that would qualify. To calculate how many children were exposed to gunfire in each school shooting, The Post relied on enrollment figures and demographic information from the U.S. Education Department, including the Common Core of Data and the Private School Universe Survey. The analysis used attendance figures from the year of the shooting for the vast majority of the schools. Credits: Research and Reporting: John Woodrow Cox, Steven Rich and Allyson Chiu Production and Presentation: John Muyskens and Monica Ulmanu Per the terms of the Creative Commons license, CISER notes that: 1. the license for this dataset is attached as the files license.htm and license.pdf. A brief version of the Creative Commons license is also included but users should familiarize themselves with the full license before using. 2. the licensed material is located at https://github.com/washingtonpost/data-school-shootings 3. Several of the files have been modified from the format presented at the above url including creating pdf versions of the documentation files and adding SAS, Stata, and SPSS versions through the use of StatTransfer 13. 4. These adapted versions of the original files are also released through the same Creative Commons license as the original with the same license elements.