In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

In 2023, the violent crime rate in the United States was 363.8 cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. In addition, due to the FBI's transition to a new crime reporting system in which law enforcement agencies voluntarily submit crime reports, data may not accurately reflect the total number of crimes committed in recent years. Reported violent crime rate in the United States The United States Federal Bureau of Investigation tracks the rate of reported violent crimes per 100,000 U.S. inhabitants. In the timeline above, rates are shown starting in 1990. The rate of reported violent crime has fallen since a high of 758.20 reported crimes in 1991 to a low of 363.6 reported violent crimes in 2014. In 2023, there were around 1.22 million violent crimes reported to the FBI in the United States. This number can be compared to the total number of property crimes, roughly 6.41 million that year. Of violent crimes in 2023, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Law enforcement officers and crime clearance Though the violent crime rate was down in 2013, the number of law enforcement officers also fell. Between 2005 and 2009, the number of law enforcement officers in the United States rose from around 673,100 to 708,800. However, since 2009, the number of officers fell to a low of 626,900 officers in 2013. The number of law enforcement officers has since grown, reaching 720,652 in 2023. In 2023, the crime clearance rate in the U.S. was highest for murder and non-negligent manslaughter charges, with around 57.8 percent of murders being solved by investigators and a suspect being charged with the crime. Additionally, roughly 46.1 percent of aggravated assaults were cleared in that year. A statistics report on violent crime in the U.S. can be found here.

In 2023, an estimated 1,21,467 violent crimes occurred in the United States. This is a decrease from the year before, when 1,256,671 violent crimes were reported. Violent crime in the United States The Federal Bureau of Investigation reported that violent crime fell nationwide in the period from 1990 to 2023. Violent crime was at a height of 1.93 million crimes in 1992, but has since reached a low of 1.15 million violent crimes in 2014. When conducting crime reporting, the FBI’s Uniform Crime Reporting Program considered murder, nonnegligent manslaughter, forcible rape, robbery and aggravated assault to be violent crimes, because they are offenses which involve force or threat of violence. In 2023, there were 19,252 reported murder and nonnegligent manslaughter cases in the United States. California ranked first on a list of U.S. states by number of murders, followed by Texas, and Florida.The greatest number of murders were committed by murderers of unknown relationship to their victim. “Girlfriend” was the fourth most common relationship of victim to offender in 2023, with a reported 568 partners murdering their girlfriends that year, while the sixth most common was “wife.” In addition, seven people were murdered by their employees and 12 people were murdered by their employers. The most used murder weapon in 2023 was the handgun, which was used in 7,1 murders that year. According to the FBI, firearms (of all types) were used in more than half of the nation’s murders. The total number of firearms manufactured in the U.S. annually has reached over 13 million units.

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.

The purpose of this project was to estimate long-term trends in violent victimization by gender and various socio-demographic factors. These factors included race and ethnicity, age, type of place (urban, suburban, rural), socio-economic status, marital status (for adults), and family status (for juveniles). The principal investigators also further disaggregated these violent victimization trends by victim-offender relationship to reveal trends in violence committed by strangers, intimate partners, and known/non-intimate offenders. The researchers produced these various trends in violent victimization by pooling and appropriately weighting the National Crime Survey and its successor, the National Crime Victimization Survey for the period 1973 to 2005, resulting in 33 years of data. In total, a series of 135 trends in violent victimization were developed.

This study examined the effect of exposure to violence on juveniles. It was specifically concerned with juveniles' perceptions of violence in schools and communities and how exposure to violence served as a risk factor for juvenile drug and alcohol use and participation in other delinquent activities. It also sought to develop a more complete picture of the context and consequences of violence in schools. The data for this study were drawn from the NATIONAL SURVEY OF ADOLESCENTS IN THE UNITED STATES, 1995 (ICPSR 2833). The data were collected through a national probability telephone sample of 4,023 juveniles and their parents or guardians. The current study drew primarily on the questions that were asked about respondents' experiences witnessing violence, their own victimization, peer and family deviance, their own delinquent activities, and drug and alcohol use.

1) Data Introduction • The Gun Violence Dataset in US is a tabularized data set for gun violence analysis that includes the date, location, victim and suspect information, and geographic coordinates of major 2024 shootings across the U.S.

2) Data Utilization (1) Gun Violence Dataset in US has characteristics that: • Each row contains key information about the shooting, including incident-specific ID, date of occurrence, state and city/county, number of deaths and injuries, suspects (death, injury, arrest), latitude, and longitude. • Data is designed to analyze the distribution of gun incidents and the extent of damage by month and region, and spatial analysis through geographic coordinates is also possible. (2) Gun Violence Dataset in US can be used to: • Analysis of shooting trends by region: Use data by location, magnitude of damage, and time to visualize and analyze the regional and temporal distribution and risk areas of gun violence. • Establishing public safety policies and prevention strategies: Based on victim and suspect information and incident characteristics, it can be used to establish effective gun control, prevention policies, resource allocation strategies, and more.

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 was a secondary analysis of data from the National Crime Victimization Survey (NCVS) and National Incidents Based Reporting System (NIBRS) for the period 1998-2007. The analysis calculates two separate measures of the incidents of violence that occurred during burglaries. The study addressed the following research questions: Is burglary a violent crime? Are different levels of violence associated with residential versus nonresidential burglaries? How frequently is a household member present during a residential burglary? How frequently does violence occur in the commission of a burglary? What forms does burglary-related violence take? Are there differences in rates of violence between attempted and completed burglaries? What constitutes the crime of burglary in current statutory law? How do the federal government and the various states define burglary (grades and elements)? Does statutory law comport with empirical observations of what the typical characteristics of acts of burglary are? The SPSS code distributed here alters an existing dataset drawn from pre-existing studies. In order to use this code users must first create the original data file drawn from National Crime Victimization Survey (NCVS) and National Incidents Based Reporting System (NIBRS) data from the period of 1998-2007. All data used for this study are publicly available through ICPSR. See the variable description section for a comprehensive list of, and direct links to, all datasets used to create this original dataset.

The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_60 _100.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_100 _250.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_250 _plus.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'total_crime': total crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'total_violent _crime': total violent crime - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft - 'tot_prop _crime': total property crime - 'arson': arson

Photo by David von Diemar on Unsplash

This study provides an evidence-based understanding on etiological issues related to school shootings and rampage shootings. It created a national, open-source database that includes all publicly known shootings that resulted in at least one injury that occurred on K-12 school grounds between 1990 and 2016. The investigators sought to better understand the nature of the problem and clarify the types of shooting incidents occurring in schools, provide information on the characteristics of school shooters, and compare fatal shooting incidents to events where only injuries resulted to identify intervention points that could be exploited to reduce the harm caused by shootings. To accomplish these objectives, the investigators used quantitative multivariate and qualitative case studies research methods to document where and when school violence occurs, and highlight key incident and perpetrator level characteristics to help law enforcement and school administrators differentiate between the kinds of school shootings that exist, to further policy responses that are appropriate for individuals and communities.

To further the understanding of violence against women, the National Institute of Justice (NIJ) and the National Center for Injury Prevention and Control (NCIPC), Centers for Disease Control and Prevention (CDC), jointly sponsored the National Violence Against Women (NVAW) Survey. To provide a context in which to place women's experiences, the NVAW Survey sampled both women and men. Completed interviews were obtained from 8,000 women and 8,005 men who were 18 years of age or older residing in households throughout the United States. The female version of the survey was fielded from November 1995 to May 1996. The male version of the survey was fielded during February to May 1996. Spanish versions of both the male and female surveys were fielded from April to May 1996. Respondents to the NVAW Survey were queried about (1) their general fear of violence and the ways in which they managed their fears, (2) emotional abuse they had experienced by marital and cohabitating partners, (3) physical assault they had experienced as children by adult caretakers, (4) physical assault they had experienced as adults by any type of perpetrator, (5) forcible rape or stalking they had experienced by any type of perpetrator, and (6) incidents of threatened violence they had experienced by any type of perpetrator. Respondents disclosing victimization were asked detailed questions about the characteristics and consequences of victimization as they experienced it, including injuries sustained and use of medical services. Incidents were recorded that had occurred at any time during the respondent's lifetime and also those that occurred within the 12 months prior to the interview. Data were gathered on both male-to-female and female-to-male intimate partner victimization as well as abuse by same-sex partners. Due to the sensitive nature of the survey, female respondents were interviewed by female interviewers. In order to test for possible bias caused by the gender of the interviewers when speaking to men, a split sample was used so that half of the male respondents had female interviewers and the other half had male interviewers. The questionnaires contained 14 sections, each covering a different topic, as follows. Section A: Respondents' fears of different types of violence, and behaviors they had adopted to accommodate those fears. Section B: Respondent demographics and household characteristics. Section C: The number of current and past marital and opposite-sex and same-sex cohabitating relationships of the respondent. Section D: Characteristics of the respondent's current relationship and the demographics and other characteristics of their spouse and/or partner. Section E: Power, control, and emotional abuse by each spouse or partner. Sections F through I: Screening for incidents of rape, physical assault, stalking, and threat victimization, respectively. Sections J through M: Detailed information on each incident of rape, physical assault, stalking, and threat victimization, respectively, reported by the respondent for each type of perpetrator identified in the victimization screening section. Section N: Violence in the respondent's current relationship, including steps taken because of violence in the relationship and whether the violent behavior had stopped. The section concluded with items to assess if the respondent had symptoms associated with post-traumatic stress disorder. Other variables in the data include interviewer gender, respondent gender, number of adult women and adult men in the household, number of different telephones in the household, and region code.

The research team collected data on homicide, robbery, and assault offending from 1984-2006 for youth 13 to 24 years of age in 91 of the 100 largest cities in the United States (based on the 1980 Census) from various existing data sources. Data on youth homicide perpetration were acquired from the Supplementary Homicide Reports (SHR) and data on nonlethal youth violence (robbery and assault) were obtained from the Uniform Crime Reports (UCR). Annual homicide, robbery, and assault arrest rates per 100,000 age-specific populations (i.e., 13 to 17 and 18 to 24 year olds) were calculated by year for each city in the study. Data on city characteristics were derived from several sources including the County and City Data Books, SHR, and the Vital Statistics Multiple Cause of Death File. The research team constructed a dataset representing lethal and nonlethal offending at the city level for 91 cities over the 23-year period from 1984 to 2006, resulting in 2,093 city year observations.

Because of their restricted access to financial resources, couples undergoing economic distress are more likely to live in disadvantaged neighborhoods than are financially well-off couples. The link between individual economic distress and community-level economic disadvantage raises the possibility that these two conditions may combine or interact in important ways to influence the risk of intimate violence against women. This study examined whether the effect of economic distress on intimate violence was stronger in disadvantaged or advantaged neighborhoods or was unaffected by neighborhood conditions. This project was a secondary analysis of data drawn from Waves 1 and 2 of the National Survey of Families and Households (NSFH) and from the 1990 United States Census. From the NSFH, the researchers abstracted data on conflict and violence among couples, as well as data on their economic resources and well-being, the composition of the household in which the couple lived, and a large number of socio-demographic characteristics of the sample respondents. From the 1990 Census, the researchers abstracted tract-level data on the characteristics of the census tracts in which the NSFH respondents lived. Demographic information contains each respondent's race, sex, age, education, income, relationship status at Wave 1, marital status at Wave 1, cohabitation status, and number of children under 18. Using variables abstracted from both Wave 1 and Wave 2 of the NSFH and the 1990 Census, the researchers constructed new variables, including degree of financial worry and satisfaction for males and females, number of job strains, number of debts, changes in debts between Wave 1 and Wave 2, changes in income between Wave 1 and Wave 2, if there were drinking and drug problems in the household, if the female was injured, number of times the female was victimized, the seriousness of the violence, if the respondent at Wave 2 was still at the Wave 1 address, and levels of community disadvantage.

Context

This dataset looks at the number of movies produced in the United States of America that fall into the "crime" genre between 1985 and 2017 and compares it to violent crime rates of the same time. The time frame was chosen based off of accessible data (The Movies Dataset ends with 2017 and the FBI's CDE tool starts at 1985).

The data for the movies and genres was pulled from "The Movies Dataset" on Kaggle where columns were adjusted and the first two genres were kept. The data was then filtered to only include films released in the United States of America from 1985-2017. Violent crime data and population data in the USA was then joined.

Tableau Public Visualization

Content

movies-to-crime_data_by_population_1985-2017_2023-03-06.csv: This file contains the filtered and sorted data joining together the rest of the included data.

movies_data_cleaned_V2.csv: This includes a large movie dataset that was pulled from the aforementioned "The Movies Dataset" and adjusted for usability for this project, find original dataset here.

population_data_1985-2017.csv: This data was pulled from the World Bank, Population, Total for United States [POPTOTUSA647NWDB], retrieved from FRED, Federal Reserve Bank of St. Louis.

violent_crime_rates_USA_1985-2017_2024-03-06.csv: This data was pulled from the Federal Bureau of Investigation's "Crime Data Explorer" tool. Data pulled includes all violent crime 1985-2017. More information concerning how violent crimes are categorized can be found on the Crime Data Explorer's website linked above.

Acknowledgements

All data was sourced via publicly available datasets and linked to above. Special thanks to Kaggle user Rounak Banik for their work creating "The Movies Dataset" which was incredibly helpful.

Inspiration

This project was a side project to gain further practice with tools such as SQL, R, Tableau and spreadsheets. It began with a focus on authors of crime novels vs amount of actual criminals. The project soon morphed into this after a struggle to find usable datasets.

The extent and consequences of various forms of interpersonal violence (IV) among college-aged persons has been well-documented. This study sought to examine how IV might differ between young adults who go to college compared to those that do not go to college. To better understand the risks for, experiences with, and consequences of IV among young adults, in fiscal year 2016, the National Institute for Justice (NIJ) made an award to Westat to fund the planning phase of a longitudinal study to research the victimization and violence experienced by college-aged individuals. The planning phase was designed to produce a comprehensive plan to conduct a generalizable, longitudinal study examining long-term trajectories of risk for, experiences with, and recovery after experiencing violence and victimization among college-aged individuals. This pilot study was the result of this planning phase. The major variables in this study contained information regarding sexual assault and rape, dating violence, stalking, violence committed by peers, and violence committed by strangers, as well as demographic variables such as participant age, gender, and race.

National IPV/SV Survey

Examining Intimate Partner and Sexual Violence in the United States

By Health [source]

About this dataset

This NISVS Intimate and Sexual Violence Survey dataset captures detailed information on intimate partner violence (IPV) and sexual violence experiences among U.S. adults aged 18 years or older. It contains statistics on the prevalence of lifetime IPV, as well as additional data on the types of intimate partner violence (psychological aggression, physical assault, sexual assault), and details more recent IPV experience; including experiencing sexual coercion or being forced to do sexual acts against one's will. Additionally, it records measures of the frequency of experiencing different forms psychological abuse; such as feeling scared by a partner's use or threat of force and feeling like one had no power over important issues in their life due to an abusive partner. Further characteristics such as respondent demographics are also included in the dataset to further explore disparities around incidence of IPV and SVP experience across various populations. With a better understanding about these trends, policy makers can take targeted action towards creating responsible legislation that addresses this pervasive problem in our society today

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How to use the dataset

This dataset provides data from the National Intimate Partner and Sexual Violence Survey (NISVS), which collects information about intimate partner violence (IPV) and sexual violence (SV). The survey was conducted by the Centers for Disease Control and Prevention from 2010-2012. This dataset includes key statistics from the surveys, with an emphasis on IPV, SV, and other types of intimate partner violence.

To get started with this dataset, take a look at the variables included in it. There are several types of variables – demographic characteristics like age; report tables that include numbers associated with different forms of IPV or SV; summary charts that show percentages associated with certain activities or events; and full reports detailing information on various topics related to IPV/SV.

For more detailed analysis, you can explore specific characteristics in different subsets of this data. For example, you might look at patterns by gender, race/ethnicity or geography. Or you could compare the frequency of certain forms of abuse over time across different groups who participated in the survey. You could also use visualizations like line graphs or scatter plots to reveal patterns between variables that were not immediately obvious when looking at only raw numbers or percentages in tables.

When analyzing results using this dataset you’ll want to be sure to take into account any potential limitations due to sampling methods used when collecting this data as well as any issues caused by variations across states’ reporting standards depending on their understanding of specific terms included in their formulation of reporting questions for participation in this survey project. It is important to keep these potential sources for variations alive when creating research questions and hypothesis associated with your own analyses related to choosing appropriate indicators as partof developing effective measuresfor comparison purposesacross differentpartici-pants participatinginthisdataset environment .

Ultimately though we hope that this dataset serves as a helpful resource when evaluating trends surrounding IPV/SV both nationally among all states included alongwith representativelocally relevantpopu- lation groups in order to promote awareness needed around monitoring preventative measures which deter people from engaginginbehaviors leading toparticularoutcomes identified through aninterpretationofthisdataset source material available via Kaggle platform interface provided hereinby subjectexpertiseand resources available within academic literature used foranalyzingdata captured within NISVS Inti/Sexualviolence Surv collection according prescribed analytical protocols suggested here- within forthiguidebooklet offeredtosupportsuchinquiries related

Research Ideas

• Examining county-level variations of national intimate partner and sexual violence incidents over time.
• Analyzing the demographics of individuals affected by such violence to better understand marginalized identities and communities at risk.
• Investigating how intimate partner and sexual violence intersects with other risk factors, including income, location, age, gender identity, race/ethnicity etc., in order to identify potential disparities in service a...

The graph shows the number of violent crime victims in the United States by gender from 2015 to 2025. The x-axis represents the years, while the y-axis indicates the number of male and female victims reported annually. Male victim counts range from a low of 181,851 in 2015 to a peak of 580,445 in 2023, while female victim counts range from 165,060 in 2015 to a high of 531,872 in 2023. Both genders show a consistent upward trend from 2015 to 2023, followed by a sharp drop in 2025. The data illustrates parallel trends for both male and female victims across the observed period.

The study assesses the extent of commonalities between individuals who become involved in violent extremist groups and criminal gangs, and the processes by which individuals engage in each group. Following this comparison, the extent to which the empirical results support the potential for anti-gang programs to bolster the resilience of communities against violent extremism and other forms of crime is assessed. Quantitative assessment was conducted by comparing individuals included in the Profiles of Individual Radicalization in the United States (PIRUS) dataset with a subset of individuals drawn from the National Longitudinal Survey of Youth 1997 (NLSY97) along a number of demographic, social, and socioeconomic characteristics. Supplementary survey data was also collected from 45 former and current gang members in the United States concurrently with long-form interviews, covering a range of variables including background characteristics, demographic information, and attitudes among the respondents.

The major goals of the project were to use survey data about victimization experiences among American women to examine: (a) the consequences of victimization for women's physical and mental health, (b) how the impact of victimization on women's health sequelae is conditioned by the victim's invoking of family and community support, and (c) how among victims of intimate partner violence, such factors as the relationship between the victim and offender, the offender's characteristics, and police involvement condition the impact of victimization on the victim's subsequent physical and mental health. This data collection consists of the SPSS syntax used to recode existing variables and create new variables from the study, VIOLENCE AND THREATS OF VIOLENCE AGAINST WOMEN AND MEN IN THE UNITED STATES, 1994-1996 (ICPSR 2566). The study, also known as the National Violence against Women Survey (NVAWS), surveyed 8,000 women 18 years of age or older residing in households throughout the United States in 1995 and 1996. The data for the NVAWS were gathered via a national, random-digit dialing sample of telephone households in the United States, stratified by United States Census region. The NVAWS respondents were asked about their lifetime experiences with four different kinds of violent victimization: sexual abuse, physical abuse, stalking, and intimidation. Using the data from the NVAWS, the researchers in this study performed three separate analyses. The study included outcome variables, focal variables, moderator variables, and control variables.

This survey of prosecutors was undertaken to describe current practice and identify "promising practices" with respect to cases involving domestic violence and child victims or witnesses. It sought to answer the following questions: (1) What are the challenges facing prosecutors when children are exposed to domestic violence? (2) How are new laws regarding domestic violence committed in the presence of children, now operating in a small number of states, affecting practice? (3) What can prosecutors do to help battered women and their children? To gather data on these topics, the researchers conducted a national telephone survey of prosecutors. Questions asked include case assignment, jurisdiction of the prosecutor's office, caseload, protocol for coordinating cases, asking about domestic violence when investigating child abuse cases, asking about children when investigating domestic violence cases, and how the respondent found out when a child abuse case involved domestic violence or when a domestic violence case involved children. Other variables cover whether police routinely checked for prior Child Protective Services (CPS) reports, if these cases were heard by the same judge, in the same court, and were handled by the same prosecutor, if there were laws identifying exposure to domestic violence as child abuse, if there were laws applying or enhancing criminal penalties when children were exposed to domestic violence, if the state legislature was considering any such action, if prosecutors were using other avenues to enhance penalties, if there was pertinent caselaw, and if the respondent's office had a no-drop policy for domestic violence cases. Additional items focus on whether the presence of children influenced decisions to prosecute, if the office would report or prosecute a battered woman who abused her children, or failed to protect her children from abuse or from exposure to domestic violence, how often the office prosecuted such women, if there was a batterers' treatment program in the community, how often batterers were sentenced to attend the treatment program, if there were programs to which the respondent could refer battered mothers and children, what types of programs were operating, and if prosecutors had received training on domestic violence issues.