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 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.

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

📊 Dataset Description This dataset contains detailed information on rape cases, covering various aspects such as incident details, outcomes, and associated legal codes. It aims to support research into the legal and social contexts of sexual violence. 🕵️‍♀️📑 🔑 Key Features of the Dataset Data on reported rape cases in [Country/Region] during the [year range]. 📋 Columns included in the dataset: headline 📰 - The headline or title of the report. district-tag 🏘️ - The district where the incident occurred. division-tag 📍 - The division categorizing the area of the incident. subdistrict-tag 🏠 - The subdistrict where the incident took place. id 🔢 - A unique identifier for each case. url 🌐 - The link to the full report, if available. last-published-at 📅 - The date when the report was last published. offset ⏳ - A data offset used for indexing or time information. content 📝 - The detailed content of the case report. meta_data 🗂️ - Metadata associated with each case, including additional tags or notes. legal_codes 📜 - A list of legal codes that were applied to the case. 📜 Includes a range of LEGAL_CODES that specify the legal framework applied to each case, such as: child_protection_act 👶 - Addresses crimes involving children. sexual_harassment_prevention_act 🚫 - Laws to prevent sexual harassment. domestic_violence_act 🏠💔 - Deals with domestic violence cases. criminal_assault_act 🥊 - Covers criminal assault offenses. public_safety_and_morality_act 🚨 - Enforces public safety and moral standards. womens_protection_act 👩🛡️ - Focuses on safeguarding women's rights and protection. kidnapping_and_coercion_act 🧑‍🤝‍🧑 - Pertains to abduction and coercion incidents. drug_and_alcohol_misuse_involvement 🍻 - Includes cases involving misuse of drugs or alcohol. attempt_to_murder 🔪 - Covers attempted murder offenses. murder_act ☠️ - Laws related to murder cases. unlawful_assembly 👥 - Addresses the unlawful gathering of people. psychological_torture_prevention 🧠⚖️ - Covers cases involving psychological abuse. witness_tampering_act 👀⚠️ - Addresses incidents of witness tampering. arbitration_and_mediation_misuse ⚖️ - Misuse of legal arbitration and mediation processes. police_misconduct_act 👮‍♂️🚫 - Deals with cases of police misconduct. 🧠 Research Applications Researchers can use this dataset for: 🔍 Investigating patterns of sexual violence and associated legal responses. 📊 Analyzing the social and legal dynamics surrounding these cases. ⚖️ Comparative studies between different LEGAL_CODES to understand their impact.

Meta Data Fields and Details This dataset contains detailed metadata about rape cases reported in Bangladesh during the year 2013-2023. The dataset is intended for researchers, policymakers, and organizations focused on understanding and addressing sexual violence. It includes information on the circumstances of each incident, the legal proceedings, the conditions of the victims, and the responses from the police and community. Each entry in the dataset provides a wealth of information that can be used for in-depth analysis and research. The metadata includes fields such as: Total Sample Size: This dataset comprises a total of 2,813 rows, each representing an individual case reported in various districts across Bangladesh. Temporal Coverage: Minimum Date: February 22, 2013 Maximum Date: April 10, 2023 Data Description: incident_details: A description of the incident, including key events and actions taken by the perpetrators. legal_proceedings: court: The name of the court handling the case. judge: The name of the judge presiding over the case. confession_date: The date when the confession was made. confession_details: Details about the confession given by the accused. victim_education_status: The education status of the victim (e.g., student, graduate). location: district: The district where the incident occurred. upazila: The sub-district or upazila where the incident occurred. road: The specific road or location within the district. victim_condition: The condition or status of the victim (e.g., stable, critical, student). is_fatal_weapon_used_in_rape: Indicates whether a fatal weapon was used in the incident (true/false). police_response: Details about the actions taken by the police in response to the incident. is_romantic_relationship: Indicates whether the incident involved a romantic relationship between the victim and the perpetrator (true/false). time_of_incident_hour: The hour when the incident occurred, if available. attacker_details: Information about the attackers, including names, ages, aliases, occupations, and residences. local_leaders_involved_in_arbitration: Indicates whether local leaders were involved in arbitration (true/false). pressure_from_attackers_family: Details about any pressure exerted by the attacker's family on the victim or their family. medical_response: Details about the medical response provided to the victim (e.g., medical examination, autopsy). community_response: Details about the community's response to the incident. is_pressure_from_attackers_family: Indicates whether there was pressure from the attacker's family (true/false). date_of_incident: The date when the incident occurred. legal_perspective: Legal perspective or interpretation related to the incident, if available. is_victim_family_filed_complaint_by_themselves: Indicates whether the victim's family filed the complaint themselves (true/false). victim_age: The age of the victim. police_involvement: Details about the involvement of the police in the case. outcome_of_arbitration: The outcome of any arbitration involving local leaders. officer_in_charge: The name of the officer in charge of the case. victim_marital_status: The marital status of the victim. victim_action: Actions taken by the victim in response to the incident (e.g., filing a complaint). number_of_attackers: The number of attackers involved in the incident. police_statement: Statements given by the police regarding the incident. motive_behind_not_filing_complaint: The motive behind not filing a complaint, if applicable. time_of_incident: The specific time of the incident, if available. public_response: The response of the public to the incident. Example Meta Data Entry for Version 2 { "victim":{ "status":"Alive", "age":19, "gender":"Female", "condition":"Garment worker", "marital_status":"Unknown", "education_status":"Unknown", "family_economic_status":"Unknown", "physical_injuries":"None", "psychological_support_provided":"Unknown" }, "attackers":{ "number_of_attackers":1, "details":[ { "name":"মুরাদ হোসেন", "age":33, "gender":"Male", "alias":"None", "occupation":"None", "residence":"None", "relationship_to_victim":"Stranger" } ] }, "incident":{ "date":"Unknown", "time":"Night", "time_hour":"11 PM", "location":"নগরের বায়েজিদ বোস্তামী থানার জালালাবাদ রেললাইনের পাশে", "details":"এক পোশাকশ্রমিক নিজের সাহসিকতায় ধর্ষণের হাত থেকে নিজেকে রক্ষা করেন। ধর্ষণের চেষ্টাকারী যুবককে পা দিয়ে ধাক্কায় দূরে সরিয়ে দেন। পরে পাহাড়ের ঝোপে লুকিয়ে থাকেন। এর মধ্যে পুলিশ এসে ধর্ষণের চেষ্টাকারী যুবককে গ্রেপ্তার করে। গতকাল রাতে নগরের বায়েজিদ বোস্তামী থানার জালালাবাদ রেললাইনের পাশে এ ঘটনা ঘটে। রাত ১১টায় কারখানায় ছুটি হওয়ার পর এক সহকর্মীকে নিয়ে ফৌজি ফ্লাওয়ার মিলসংলগ্ন রেললাইনের পাশে বাসা দেখতে যাচ্ছিলেন। ওই সময় মুরাদ হোসেন তাঁর সহকর্মীকে আটকে মারধর করতে থাকেন। পরে মুরাদের সহযোগীরা তাঁর সহকর্মীকে নিয়ে যান। এদিকে মুরাদ তাঁকে টেনেহিঁচড়ে রেললাইনের পাশে পাহাড়ে নিয়ে যান। একপর্যায়ে তাঁকে মাটিতে ফেলে দেন। ওই সময় তিনি পা দিয়ে মুরাদের মুখে আঘাত করেন। এতে মুরাদ যখন মাটিতে পড়ে যান,...

The dataset contains annual count data for the number of family-related domestic incident reports, family-related felony assaults, domestic violence related felony assaults, family-related rapes and domestic violence related rapes. The Mayor's Office to End Domestic and Gender-Based Violence (ENDGBV) develops policies and programs, provides training and prevention education, conducts research and evaluations, performs community outreach, and operates the New York City Family Justice Centers. The office collaborates with City agencies and community stakeholders to ensure access to inclusive services for survivors of domestic and gender-based violence (GBV) services. GBV can include intimate partner and family violence, elder abuse, sexual assault, stalking, and human trafficking. ENDGBV operates the New York City Family Justice Centers. These co‐located multidisciplinary domestic violence service centers provide vital social service, civil legal and criminal justice assistance for survivors of intimate partner violence and their children under one roof. The Brooklyn Family Justice Center opened in July 2005; the Queens Family Justice Center opened in July 2008; the Bronx Family Justice Center opened in April 2010; Manhattan Family Justice Center opened in December 2013 and Staten Island Family Justice Center opened in June 2015. ENDGBV also has a Policy and Training Institute that provides trainings on intimate partner violence to other City agencies. The New York City Healthy Relationship Academy, with is part of the Policy and Training Institute, provides peer lead workshops on healthy relationships and teen dating violence to individuals between the age of 13 and 24, their parents and staff of agencies that work with youth in that age range. The dataset is collected to produce an annual report on the number of family-related and domestic violence related incidents that occur at the community board district level in New York City. The New York City Police Department provides ENDGBV with count data on: family-related domestic incident reports, family-related felony assaults, domestic violence felony assaults, family-violence related rapes and domestic violence related rapes.

The National Crime Victimization Survey (NCVS), previously called the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. Beginning in 1992, the survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual assault, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime by various subpopulations. This dataset represents the concatenated version of the NCVS on a collection year basis for 1992-2023. A collection year contains records from interviews conducted in the 12 months of the given year. Under the collection year format, victimizations are counted in the year the interview is conducted, regardless of the year when the crime incident occurred.For additional information on the dataset, please see the documentation for the data from the most current year of the NCVS, ICPSR Study 38962.

In 2022, the total number of rape cases reported in India amounted to over 31 thousand. This was a slight decrease in rape cases compared to the previous year. Even though many rapes are not reported in the country, it is an issue that continuously makes news headlines, some leading to public protests. Although reports of rape have increased in recent years, it was still associated with shame for the victim, rather than the perpetrator. The justice system  A victim of rape in India not only experiences social stigmatization but what is more, her fight for justice is not made easy due to the system that often faults the victim for their misfortune. Instances have been reported where victims are confronted with hostile conditions at police stations and have been often pressured to withdraw their cases. However, once a case goes to trial, it can take decades before anything is resolved. Rape cases in particular, face huge backlog where the number of new cases supersede the number of cases disposed every year. The process is arduous and could add so much trauma to the victim’s life that they often buckle under pressure from family of their own or that of the perpetrator.  Women in India India is known to be one of the most dangerous countries in the world for women. Indian women are constantly in a state of high alert when alone on the streets, at work or in the markets. Due to India’s predominantly patriarchal nature, domestic violence is known to be culturally acceptable. Studies reveal that even a majority of working women suffer domestic abuse from their husbands. A non-earning woman’s position further exacerbates vulnerability and dependence on their male partner as opposed to a woman who contributors financially to the household. Rampant poverty across the country is the main driver for low literacy rates and consequently, disempowerment and abuse among women.

This dataset shows City level data for all over the United States, and has various attributes for different crimes. Cities are shown as Latitude and longitude points. Attributes include murder, manslaughter, violent crimes, arson, motor vehicle theft, property crimes, aggravated assault, burglary, larceny, theft, and rape. Data was provided by the Federal Bureau of Investigation. Source: FBI URL: http://www.fbi.gov/ucr/cius2006/data/table_08.html

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.

This collection contains electronic versions of the Uniform Crime Reports publications for the early years of the Uniform Crime Reporting Program in the United States. The reports, which were published monthly from 1930 to 1931, quarterly from 1932 to 1940, and annually from 1941 to 1959, consist of tables showing the number of offenses known to the police as reported to the Federal Bureau of Investigation by contributing police departments. The term "offenses known to the police" includes those crimes designated as Part I classes of the Uniform Classification code occurring within the police jurisdiction, whether they became known to the police through reports of police officers, citizens, prosecuting or court officials, or otherwise. They were confined to the following group of seven classes of grave offenses, historically those offenses most often and most completely reported to the police: felonious homicide, including murder and nonnegligent manslaughter, and manslaughter by negligence, rape, robbery, aggravated assault, burglary -- breaking and entering, and larceny -- theft (including thefts $50 and over, and thefts under $50, and auto theft). The figures also included the number of attempted crimes in the designated classes excepting attempted murders classed as aggravated assaults. In other words, an attempted burglary or robbery, for example, was reported in the same manner as if the crimes had been completed. "Offenses known to the police" included, therefore, all of the above offenses, including attempts, which were reported by the police departments and not merely arrests or cleared cases.

The dataset contains annual count data for the number of intimate partner related domestic incident reports, intimate partner-related felony assaults, domestic violence related felony assaults, intimate partner-related rapes and domestic violence related rapes. The Mayor's Office to Combat Domestic Violence (OCDV) formulates policies and programs, coordinates the citywide delivery of domestic violence services and works with diverse communities and community leaders to increase awareness of domestic violence. OCDV collaborates closely with government and nonprofit agencies that assist domestic violence survivors and operates the New York City Family Justice Centers. These co‐located multidisciplinary domestic violence service centers provide vital social service, civil legal and criminal justice assistance for survivors of intimate partner violence and their children under one roof. OCDV also has a Policy and Training Institute that provides trainings on intimate partner violence to other City agencies. The New York City Healthy Relationship Academy, with is part of the Policy and Training Institute, provides peer lead workshops on healthy relationships and teen dating violence to individuals between the age of 13 and 24, their parents and staff of agencies that work with youth in that age range. The dataset is collected to produce an annual report on the number of family-related and domestic violence related incidents that occur at the community board district level in New York City. The New York City Police Department provides OCDV with count data on: Intimate partner related domestic incident reports, intimate partner related felony assaults, domestic violence felony assaults, intimate partner related rapes and domestic violence related rapes.

The purpose of this study was to use data from the National Crime Survey (NCS) and the National Crime Victimization Survey (NCVS) to explore whether the likelihood of police notification by rape victims had increased between 1973-2000. To avoid the ambiguities that could arise in analyses across the two survey periods, the researchers analyzed the NCS (1973-1991) and NCVS data (1992-2000) separately. They focused on incidents that involved a female victim and one or more male offenders. The sample for 1973-1991 included 1,609 rapes and the corresponding sample for 1992-2000 contained 636 rapes. In their analyses, the researchers controlled for changes in forms of interviewing used in the NCS and NCVS. Logistic regression was used to estimate effects on the measures of police notification. The analyses incorporated the currently best available methods of accounting for design effects in the NCS and NCVS. Police notification served as the dependent variable in the study and was measured in two ways. First, the analysis included a polytomous dependent variable that contrasted victim reported incidents and third-party reported incidents, respectively, with nonreported incidents. Second, a binary dependent variable, police notified, also was included. The primary independent variables in the analysis were the year of occurrence of the incident reported by the victim and the relationship between the victim and the offender. The regression models estimated included several control variables, including measures of respondents' socioeconomic status, as well as other victim, offender, and incident characteristics that may be related both to the nature of rape and to the likelihood that victims notify the police.