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.

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. Analyses from the Crime Survey for England and Wales (CSEW).

Context

This is clean data that contains many statistics about general assaults, robbery, and sexual harassment between 2015, and it shows the exact percentage for that year, and it is ready to work on it and do the analysis directly.

You can also work on this data, it is also ready to work here: 1. Abortion-statistics-year-ended-december-2019 2. injurystatisticsworkrelatedclaims2018 3. Effectsofcovid19ontradeat24march2021 4. Businesspriceindexesdecember2020

The Bureau of Justice Statistics (BJS) collects and analyzes data on the incidence and effects of sexual violence in prisons and jails. The data, in various datasets, are collected from individuals currently and formerly in federal, state, county, and municipal facilities. The data are collected using a multiple-measure, multiple-mode data collection strategy. Data sets in this series include surveys and other statistical studies, including the National Inmate Survey (NIS), the Former Prisoner Survey (FPS), and the National Survey of Youth in Custody (NSYC).

This dataset reflects reported incidents of crime that have occurred in the City of Chicago over the past year, minus the most recent seven days of data. 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. Any use of the information for commercial purposes is strictly prohibited. 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.

The primary research objective of this study was to examine the prevalence, nature, and reporting of various types of sexual assault experienced by university students in an effort to inform the development of targeted intervention strategies. In addition, the study had two service-oriented objectives: (1) to educate students about various types of sexual assault, how they can maximize their safety, and what they can do if they or someone they know has been victimized and (2) to provide students with information about the campus and community resources that are available should they need assistance or have any concerns or questions. The study involved a Web-based survey of random samples of undergraduate students at two large public universities, one located in the South (University 1) and one located in the Midwest (University 2). Researchers drew random samples of students aged 18-25 and enrolled at least three-quarters' time at each university to participate in the study. The survey was administered in the winter of 2005-2006, and a total of 5,446 undergraduate women and 1,375 undergraduate men participated for a grand total of 6,821 respondents. Sampled students were sent an initial recruitment e-mail that described the study, provided a unique study ID number, and included a hyperlink to the study Web site. During each of the following weeks, students who had not completed the survey were sent follow-up e-mails and a hard-copy letter encouraging them to participate. The survey was administered anonymously and was designed to be completed in an average of 15 minutes. Respondents were provided with a survey completion code that, when entered with their study ID number at a separate Web site, enabled them to obtain a $10 Amazon.com gift certificate. The survey was divided into six modules. The Background Information module included survey items on demographics, school classification (year of study, year of enrollment, transfer status), residential characteristics, academic performance, and school involvement. An Alcohol and Other Drug Use module generated a number of measures of alcohol and drug use, and related substance use behaviors. A Dating module included items on sexual orientation, dating, consensual sexual activity, and dating violence. The Experiences module was developed after extensive reviews of past surveys of sexual assault and generated information on physically forced sexual assault and incapacitated sexual assault. For both physically forced and incapacitated sexual assault, information was collected on completed and attempted assaults experienced before entering college and since entering college. For male respondents, a Behaviors module asking about the perpetration of the same types of sexual assault covered in the Experiences module was included. The final module of the survey covered attitudes about sexual assault and attitudes about the survey. The data file contains 747 variables.

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.

The dataset contains year-, state-, type-of-crime- and gender-wise compiled data on the number of different types of crimes which were committed against children and the number of victims who were affected by the same crimes. The different types of crimes covered in the dataset include kidnapping and abduction crimes such as kidanapping and abduction for the purpose of murder, begging, ransom, compelling for marriage, procuration of minor girls, importation of girls from foreign countries, missing deemed as kidnapped, etc., fatal crimes such as murder, attempt to commit murder, muder with rape, abetment of suicide of child, infanticide, foeticide, trafficking and sexual crimes such buying and selling of minors for prostitution, use of children for pornography, transmiting sexual content and material involving children in sexually explicit acts, sexual assualt, penetrative sexual assault, rape, and other crimes such as child labour, child marriage, exposure, abandaonment, simple hurt, grievous hurt, insult and assualt of damage modesty, crimes under juvenile justice act and transplantation of organs act, etc.

The dataset also categorizes the above crimes by the pertinent legislations and their specific secitons against which the crimes have been committed against children.

Note: The rate of crimes in the dataset refers to number of crimes committed against Children by projected population of children in Lakhs

This qualitative study explored incidents of sexual assault of women by former husbands or cohabitants and the link to male peer support for sexually aggressive men in rural Ohio. Sexual assault was defined as unwanted sexual contact, sexual coercion, attempted rape, or rape. A series of screening questions were asked to determine a respondent's eligibility for inclusion in the study. The main criteria were being aged 18 or older and having ever had any type of unwanted sexual experience when they wanted to end, were trying to end, or after they had ended a relationship with a husband or live-in male partner. If they met the selection criteria, the women were invited to a semi-structured face-to-face interview at a time and place of their choosing. Between February 2003 and July 2004, 43 women were interviewed. The interviews included several demographic questions such as income, level of education, marital status, length of the relationship, and how long the respondent had lived in the area. Other questions asked about the unwanted sexual experiences, social support networks, and male pornography use.

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 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.

This dataset contains the tweet ids of 1,098,567 tweets, including tweets between October 1, 2019 and December 31, 2019. 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 datasetBecause of the size of the files, the list of identifiers are split in 2 files containing 1,000,000 ids each.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 still available (not deleted by users) tools like Hydrator are availableThere are similar subsets related to the Schlesinger Library #metoo Digital Media Collection available in this dataverse

Anti-social behaviour (ASB) outcomes for disabled people in England and Wales aged 16 and over, with analysis by disability status, country, sex, age, impairment type, type of ASB. Domestic abuse and sexual assault outcomes for disabled people in England and Wales aged 16 to 59 years, with analysis by disability status, age, sex, impairment type, impairment severity, country and region. All outcomes using the Crime Survey for England and Wales (CSEW) data.

This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: All businesses identified as victims in CPD data have been removed from this dataset.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

Abstract copyright UK Data Service and data collection copyright owner.

The study examined in detail over 300 criminal trials surviving in Geneva relating to sexual deviance (homosexuality, male rape/sexual assault, paedophilia, lesbianism, bestiality, adolescent sexual experimentation, female rape/sexual assault, adultery and fornication). These trials, in which verbatim testimony and numerous depositions by witnesses survive, give an ideal place to test pre-Freudian ideas of sexual development, sexual categories and sexual self-awareness.
Main Topics:

The data collection contains details of over 1000 individuals gleaned from over 300 trials for the period c.1440 - c.1790 (although the overwhelming bulk of of the data come from the period 1530 - 1680). This represents, on average, over six people per year directly involved either as defendants or witnessess in trials relating to deviant, criminalised or violent sexual conduct. The database does not include the large number of magistrates who would have been present as judges and observers.

This large number of 'participants' as well as the excellent and detailed information preserved in the trial dossiers means that it has been possible to identify extremely subtle yet consistent ideas of sexuality and sexual preference among judges, defendants and witnesses. The voices of the 'deviants' are sufficiently evident to evaluate early modern views on sexuality, sexual identity and sexual preference. These views have been compared with early modern ideas as well as modern ideas about the development of these assumptions and presuppositions in an historiographical context. It has been demonstrated that the participants in these trials had very clear ideas of differing types of deviancy as well as firm convictions that criminals came to these types of crimes through diverse paths of sexual development.

The main variables include: the gender, age, occupation, place of origin and civic status of defendants and witnesses; the names and civic status of their parents and spouse; the crime they were charged with details of the interrogation, verdict and sentence; and cross references between cases.

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

Analysis of ‘Police Incidents’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3c21a355-8ca1-401e-9ee4-4bec6979341d on 12 February 2022.

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

Explore Crime and Safety data from the Cary Police Department.

This data is extracted by the Town of Cary's Police Department's RMS application.

The police incidents will provide data on the Part I crimes of arson, motor vehicle thefts, larcenies, burglaries, aggravated assaults, robberies and homicides. Sexual assaults and crimes involving juveniles will not appear to help protect the identities of victims.

This dataset includes criminal offenses in the Town of Cary for the previous 10 calendar years plus the current year. The data is based on the National Incident Based Reporting System (NIBRS) which includes all victims of person crimes and all crimes within an incident. The data is dynamic, which allows for additions, deletions and/or modifications at any time, resulting in more accurate information in the database. Due to continuous data entry, the number of records in subsequent extractions are subject to change. Crime data is updated daily however, incidents may be up to three days old before they first appear.

About Crime Data

The Cary Police Department strives to make crime data as accurate as possible, but there is no avoiding the introduction of errors into this process, which relies on data furnished by many people and that cannot always be verified. Data on this site are updated daily, adding new incidents and updating existing data with information gathered through the investigative process.

This dynamic nature of crime data means that content provided here today will probably differ from content provided a week from now. Additional, content provided on this site may differ somewhat from crime statistics published elsewhere by other media outlets, even though they draw from the same database.

Withheld Data

In accordance with legal restrictions against identifying sexual assault and child abuse victims and juvenile perpetrators, victims, and witnesses of certain crimes, this site includes the following precautionary measures: (a) Addresses of sexual assaults are not included. (b) Child abuse cases, and other crimes which by their nature involve juveniles, or which the reports indicate involve juveniles as victims, suspects, or witnesses, are not reported at all.

Certain crimes that are under current investigation may be omitted from the results in avoid comprising the investigative process.

Incidents five days old or newer may not be included until the internal audit process has been completed.

This data is updated daily.

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

Sexual Violence Awareness Month (SVA Month) is held during October each year to: raise community awareness about sexual violence promote the support options available to people affected by sexual assault and sexual abuse uphold a clear message that sexual violence will not be tolerated in our communities. Please use the assets in this toolkit to promote the month to your networks. Find out more about SVA Month.

This dataset contains Crime and Safety data from the Cary Police Department.

This data is extracted by the Town of Cary's Police Department's RMS application. The police incidents will provide data on the Part I crimes of arson, motor vehicle thefts, larcenies, burglaries, aggravated assaults, robberies and homicides. Sexual assaults and crimes involving juveniles will not appear to help protect the identities of victims.

This dataset includes criminal offenses in the Town of Cary for the previous 10 calendar years plus the current year. The data is based on the National Incident Based Reporting System (NIBRS) which includes all victims of person crimes and all crimes within an incident. The data is dynamic, which allows for additions, deletions and/or modifications at any time, resulting in more accurate information in the database. Due to continuous data entry, the number of records in subsequent extractions are subject to change. Crime data is updated daily however, incidents may be up to three days old before they first appear.

About Crime Data

The Cary Police Department strives to make crime data as accurate as possible, but there is no avoiding the introduction of errors into this process, which relies on data furnished by many people and that cannot always be verified. Data on this site are updated daily, adding new incidents and updating existing data with information gathered through the investigative process.

This dynamic nature of crime data means that content provided here today will probably differ from content provided a week from now. Additional, content provided on this site may differ somewhat from crime statistics published elsewhere by other media outlets, even though they draw from the same database.

Withheld Data

In accordance with legal restrictions against identifying sexual assault and child abuse victims and juvenile perpetrators, victims, and witnesses of certain crimes, this site includes the following precautionary measures: (a) Addresses of sexual assaults are not included. (b) Child abuse cases, and other crimes which by their nature involve juveniles, or which the reports indicate involve juveniles as victims, suspects, or witnesses, are not reported at all.

Certain crimes that are under current investigation may be omitted from the results in avoid comprising the investigative process.

Incidents five days old or newer may not be included until the internal audit process has been completed.

This data is updated daily.

This dataset comprises survey responses collected from individuals regarding the increasing incidents of rape in Bangladesh. The responses were gathered using a form and contain insights into the participants' views on the causes, prevention methods, and personal experiences related to rape and sexual harassment. The dataset consists of a total of 116 entries and 11 columns. Here is a detailed description of the columns: Timestamp: The date and time when the survey response was submitted. Gender: The gender of the respondent. Reasons for the increase in rape cases: Respondents' opinions on why rape incidents have increased in recent years in Bangladesh. Why do girls fall victim to rape?: Respondents' views on why girls become victims of rape. Other reasons why girls fall victim to rape: Additional reasons provided by respondents on why girls become victims of rape. Have you known anyone in your surroundings who has been a victim of harassment or unpleasant situations?: Indicates whether respondents know someone who has been a victim of harassment or unpleasant situations. Description of harassment experiences in surroundings: Descriptions of harassment experiences shared by respondents. Number of female members in the respondent's family: The number of female members in the respondent's family. Do you think it is possible to create a rape-free society?: Respondents' opinions on whether a rape-free society is achievable. How do you think rape can be prevented?: Suggestions provided by respondents on how to prevent rape. What do you think should be done from your position?: Actions that respondents believe they can take to contribute to preventing rape.