This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

In 2023, Texas had the highest number of forcible rape cases in the United States, with 15,097 reported rapes. Delaware had the lowest number of reported forcible rape cases at 194. Number vs. rate It is perhaps unsurprising that Texas and California reported the highest number of rapes, as these states have the highest population of states in the U.S. When looking at the rape rate, or the number of rapes per 100,000 of the population, a very different picture is painted: Alaska was the state with the highest rape rate in the country in 2023, with California ranking as 30th in the nation. The prevalence of rape Rape and sexual assault are notorious for being underreported crimes, which means that the prevalence of sex crimes is likely much higher than what is reported. Additionally, more than a third of women worry about being sexually assaulted, and most sexual assaults are perpetrated by someone the victim knew.

This dataset shows the statistics for reported rapes for the period 2003 - 2010 by country. The data also shows the rate expressed as rapes per 100,000 people. The 'latest' column shows the most recent rate per country. It is important to note that this dataset only shows recorded rates and many countries do not publish this information (recorded as zero). Of course, rape is not always reported so actual instances may be much higher. Data sourced from http://en.wikipedia.org/wiki/Rape_statistics and country boundaries from http://www.sharegeo.ac.uk/handle/10672/124. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-09-13 and migrated to Edinburgh DataShare on 2017-02-21.

Nature of sexual assault by rape or penetration experienced by adults since the age of 16 years, including breakdowns by age, sex, victim-perpetrator relationship, location and other factors, based on findings from the Crime Survey for England and Wales (CSEW).

This study had four key goals. The first goal was to identify how many women in the United States and in college settings have ever been raped or sexually assaulted during their lifetime and within the past year. The next goal was to identify key case characteristics of drug-facilitated and forcible rapes. The third goal was to examine factors that affect the willingness of women to report rape to law enforcement or seek help from their support network. The last goal was to make comparisons between the different types of rape. Part 1 (General Population) data consisted of a national telephone household sample of 3,001 United States women, whereas Part 2 (College Population) data consisted of 2,000 college women selected from a reasonably representative national list of women attending four year colleges and universities. Both data parts contain the same 399 variables. Interviews were completed between January 23 and June 26, 2006. Respondents were asked questions regarding risk perception, fear of violence, and accommodation behavior. The women were also asked their opinions and attitudes about reporting rape to the authorities and disclosing rape to family members, peers, or other individuals. This includes questions about barriers to reporting and experiences that women have had being the recipient of a disclosure from a friend, relative, or other individual. The respondents were asked a series of questions about rape, including different types of forcible, drug- or alcohol-facilitated, and incapacitated rape. For women who endorsed one or more rape experiences, a wide range of rape characteristics were assessed including characteristics around the nature of the event, perpetrator-victim relationship, occurrence of injury, involvement of drugs or alcohol, receipt of medical care, and whether the rape was reported to the authorities. The respondents were also asked a series of questions regarding substance use, including prescription and illegal drugs and alcohol. Additionally, a series of questions related to post-traumatic stress disorder and depression were asked. Finally, the women were asked to provide basic demographic information such as age, race, ethnicity, and income.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) for all complete quarters so far this year (2016). For additional details, please see the attached data dictionary in the ‘About’ section.

About Violence Against Women & Girls

The Demographic and Health Surveys (DHS) Program exists to advance the global understanding of health and population trends in developing countries.

The UN describes violence against women and girls (VAWG) as: “One of the most widespread, persistent, and devastating human rights violations in our world today. It remains largely unreported due to the impunity, silence, stigma, and shame surrounding it.”

In general terms, it manifests itself in physical, sexual, and psychological forms, encompassing: • intimate partner violence (battering, psychological abuse, marital rape, femicide) • sexual violence and harassment (rape, forced sexual acts, unwanted sexual advances, child sexual abuse, forced marriage, street harassment, stalking, cyber-harassment), human trafficking (slavery, sexual exploitation) • female genital mutilation • child marriage

About The Data

The data was taken from a survey of men and women in African, Asian, and South American countries, exploring the attitudes and perceived justifications given for committing acts of violence against women. The data also explores different sociodemographic groups that the respondents belong to, including: Education Level, Marital status, Employment, and Age group.

It is, therefore, critical that the countries where these views are widespread, prioritize public awareness campaigns, and access to education for women and girls, to communicate that violence against women and girls is never acceptable or justifiable.

Question | Respondents were asked if they agreed with the following statements: - A husband is justified in hitting or beating his wife if she burns the food - A husband is justified in hitting or beating his wife if she argues with him - A husband is justified in hitting or beating his wife if she goes out without telling him - A husband is justified in hitting or beating his wife if she neglects the children - A husband is justified in hitting or beating his wife if she refuses to have sex with him - A husband is justified in hitting or beating his wife for at least one specific reason

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The purpose of this study was to provide an in-depth look at rapes and attempted rapes in the United States. Part 1 of the collection offers data on rape victims and contains variables regarding the characteristics of the crime, such as the setting, the relationship between the victim and offender, the likelihood of injury, and the reasons why rape is not reported to police. Part 2 contains data on a control group of females who were victims of no crime or of crimes other than rape. The information contained is similar to that found in Part 1.

This study was an evidence-based review of sexual assault preventive intervention (SAPI) programs. A total of 67 publications including articles, government reports, and book chapters (excluding dissertations) representing 59 studies met the inclusion criteria and were included in the data abstraction process. In order to be included in the review, the resource had to be an English-language publication, published between 1990 and June 2003, of a SAPI evaluation of a primary or secondary preventive intervention program that targeted people who were adolescent-age or older, and which included outcome measures and a pre-test/post-test or between-group differences design. The findings for the article reviews are presented in evidence tables, for the general population in Part 1 and the evidence tables for individuals with disabilities in Part 2.

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 objective of the present study was to examine the direct and indirect impacts of childhood sexual abuse on maternal attitudes, perceptions, and behavior. The study's participants were a subset of 357 primiparous women interviewed at 28 to 32 weeks' gestation between the fall of 1990 and early 1992. At the time of the initial interview, almost 35% of the women reported sexual abuse before age 18. In 1995 and 1996, 265 women, 74% of the original sample, were re-interviewed when their children were between two and fours years old. In this sample 40% of the respondents had been identified as sexually abused in the first study. In the follow-up interview, variables measuring parenting outcomes included: child-rearing competence, satisfaction, and efficacy; parenting stress; discipline practices; and family functioning. Variables measuring possible mediating factors between a history of sexual abuse and parenting practices included: education, occupation, income, family structure; current physical and mental health parameters, particularly depressive symptomatology; perceived current stresses unrelated to parenting; current family violence or sexual victimization; and parental sense of mastery. The data file distributed for this study contains 265 cases and 556 variables.

Investigators: Benedict, Mary

Context

The Uniform Crime Reporting (UCR) Program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.

Today, four annual publications, Crime in the United States, National Incident-Based Reporting System, Law Enforcement Officers Killed and Assaulted, and Hate Crime Statistics are produced from data received from over 18,000 city, university/college, county, state, tribal, and federal law enforcement agencies voluntarily participating in the program. The crime data are submitted either through a state UCR Program or directly to the FBI’s UCR Program.

This dataset focuses on the crime rates and law enforcement employment data in the state of California.

Content

Crime and law enforcement employment rates are separated into individual files, focusing on offenses by enforcement agency, college/university campus, county, and city. Categories of crimes reported include violent crime, murder and nonnegligent manslaughter, rape, robbery, aggravated assault, property crime, burglary, larceny-theft, motor vehicle damage, and arson. In the case of rape, data is collected for both revised and legacy definitions. In some cases, a small number of enforcement agencies switched definition collection sometime within the same year.

Acknowledgements

This dataset originates from the FBI UCR project, and the complete dataset for all 2015 crime reports can be found here.

Inspiration

• What are the most common types of crimes in California? Are there certain crimes that are more common in a particular place category, such as a college/university campus, compared to the rest of the state?
• How does the number of law enforcement officers compare to the crime rates of a particular area? Is the ratio similar throughout the state, or do certain campuses, counties, or cities have a differing rate?
• How does the legacy vs. refined definition of rape differ, and how do the rape counts compare? If you pulled the same data from FBI datasets for previous years, can you see a difference in rape rates over time?

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

ABSTRACT CONTEXT AND OBJECTIVE: Sexual violence is increasingly frequent worldwide. The aim here was to evaluate the sociodemographic and psychological characteristics of women who requested legal abortion, at a public healthcare service, after sufering sexual violence. DESIGN AND SETTING: Retrospective descriptive study on 131 women who underwent legal abortion at the University of Campinas between 1994 and 2014, consequent to sexual violence. METHODS: The sociodemographic and psychological characteristics of women who were victims of sexual violence were evaluated from their medical records. The tests used to evaluate possible associations were the chi-square and/or Fisher’s exact test. RESULTS: The women’s mean age was 23 ± 9.2 years; 77.9% were white and 71.8% were single; 32.8% were students and 58.6% had employment outside of their homes. The majority reported that they did not know the aggressor (62.3%), but among the adolescents, 58% of the aggressors were known. The majority asked for abortion up to the 12th weeks of gestation (63.4%). Only 2.3% presented curettage complications. The psychological situation most frequently encountered was determined, in 34.4% of the cases before the abortion; and good in 32.8% after the abortion. CONCLUSIONS: There was greater occurrence of sexual violence among students and women who worked outside. Among the students, most of these were adolescents and had no previous sexual life. The teenagers were raped by a known aggressor.

This dataset contains the tweet ids of 407,911 tweets, including tweets between October 1, 2021 and December 31, 2021. This collection is a subset of the Schlesinger Library #metoo Digital Media Collection.These tweets were collected weekly from the Twitter API through Social Feed Manager using the POST statuses/filter method of the Twitter Stream API.Please note that there will be no updates to this dataset.The following list of terms includes the hashtags used to collect data for this dataset: #metoo, #timesup, #metoostem, #sciencetoo, #metoophd, #shittymediamen, #churchtoo, #ustoo, #metooMVMT, #ARmetoo, #TimesUpAR, #metooSociology, #metooSexScience, #timesupAcademia, and #metooMedicine.Be aware that previous quarters (up to the first quarter of 2020) only include one hashtag: #metoo.Per Twitter's Developer Policy, tweet ids may be publicly shared for academic purposes; tweets may not. Therefore, this dataset only contains tweet ids. In order to retrieve tweets that are still available (not deleted by users) tools like Hydrator are available.There are similar subsets related to the Schlesinger Library #metoo Digital Media Collection available by quarter, as well as a full dataset with a larger corpus of hashtags.

This dataset reflects incidents that have been reported to the New Orleans Police Department in 2023. Data is provided by Orleans Parish Communication District (OPCD), the administrative office of 9-1-1 for the City of New Orleans. Please request 911 audio via our public records request system here: https://nola.nextrequest.com.

In the OPCD system, NOPD may reclassify or change the signal type for up to 36 hours after the incident is marked up. For information about an incident after this time period, citizens may request police reports from the NOPD Public Records Division. In order to protect the privacy of victims, addresses are shown at the block level and the call types cruelty to juveniles, juvenile attachment and missing juvenile have been removed in accordance with the Louisiana Public Records Act, L.R.S. 44:1. Map coordinates (X,Y) have been removed for the following call types: Aggravated Rape, Aggravated Rape - MA, Crime Against Nature, Mental Patient, Oral Sexual Battery, Prostitution, Sexual Battery, Simple Rape, Simple Rape - Male V, and Soliciting for Prost.

This excel file contains the data from our survey with 117 participants who contributed to the #MeToo hashtag. Participants were mostly from Europe and Australasia. Most identified as women, but a few men responded as well. The survey asks about the experiences of contributing to the hashtag, why people did (not) share a personal experience, and what potential they feel the #MeToo movement has for making broader structural changes.We have also published a chapter based on the dataset:Mendes, K. & Ringrose, J. (2019) ‘Digital Feminist Activism: #MeToo and the everyday experiences of challenging rape culture’ in Bianca Fileborn and Rachel Loney-Howes (eds.) #MeToo & the politics of social change. Basingstoke: Palgrave Macmillan.

Crime Trends in India from 2001 to 2020

A Statistical Overview of Criminal Victimization and Offender Action

By Rajanand Ilangovan [source]

About this dataset

This Dataset provides an up-to-date analysis of crime trends in India from 2001 to the present. It contains complete information about different types of crimes such as rape, murder, and theft that were committed across India. By analyzing this dataset we can determine the areas where crimes were most prevalent, what type of offenders were usually involved in the crime and which year had the highest number of registered cases. Additionally, we can also analyse which group experienced most complaints and what kind of punishments or consequences they faced like departmental enquiries, magisterial enquiries or police personnel trials completed. This data set is perfect for further research into crime trends in India and will help us better understand why certain types of crimes take place more frequently than others

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How to use the dataset

• Area Name (state or UT) where the crime was reported. • Year in which the crime was reported. • Subgroup (type of crime). • Number of cases registered, number of cases reported for departmental action etc., related to a particular type of crime and state/UT.
• Number of complaints/cases declared false/unsubstantiated, number of police personnel convictions etc., related to a particular type of crime and state/UT.
• Number of cases in which offenders were others known persons to the victims, neighbours or relatives to the victims etc., related to a particular type of crime and state/UT.

By studying this dataset one might explore different angles by analysing factors like:

• What are the top states with high rate criminal activities? Which areas are relatively safer?
• Are any states witnessing higher incidences than national average levels? Alternatively, are there any regions which have recorded lower rates than national average levels?
• What is trend between sub crimes across India both regional & time wise? How has it changed over time ? (2001-20) ;
Movement among crimes on monthly basis during period 2001 - 2020 Comparison among ages , genders & professions involved with Crime Rates && Timeline comparison between Types Of Crime , Crimes Involving Police Personnel Contractors in Crimes as timeline . Immigration Report . Is absolute difference btw urban & rural up from previous years ? Open conversations about what government efforts need more focus & why . Fundamentals impacting reducing / increasing rate behind closed doors . Any impactful key insights about SelfDefence Degree given out that year highlighting decreasing / increasing amount if increase thenwhat extra activity got curated btw that law was enacted vs before enactment if possible Outliers Analysis on same murders done by pediphiles or sexual assault against women under minorities if exists

Research Ideas

• Analyzing crime trends over time by analyzing the Year, Sub_group and Area_Name columns to understand different types of crimes and patterns of criminal activity in India.

• Evaluating the effectiveness of police response to different types of crimes, such as comparing the CPA_-_Cases_Registered, CPA_-_Cases_Reported_for_Dept._Action and CPB_-_Police_PersonnelAcquitted data fields across different time periods, sub-groups and areas to assess how well law enforcement is responding to crimes reported.

• Tracking changes in punishment awarded for different crimes by analyzing the CPC_-_Police_-Personnel_-Major-Punishment_-awarded data field for changes over ti...