This study offers novel insights into mechanisms associated with sexual assault (SA) among sexual minority women (SMW). Experiences of bias and stigma contribute to lower rates of SA reporting by this population. This results in victims with unmet needs and fewer criminal prosecutions of SA perpetrators. This study used a mixed-methods approach to collect data from lesbian, bisexual, and heterosexual women to instigate changes that would improve responses from law enforcement, victim services, and anti-violence programs that serve SMW. This study comprised of three parts a: baseline survey, qualitative interview, and daily survey. Self-reported baseline questionnaires included topics like lifetime victimization (childhood sexual abuse, adult sexual aggression, and assault), discrimination, distress, mental health, alcohol use, and sexual history. The qualitative interviews focused on the most recent, and when applicable, the most salient adult sexual assault (ASA) incident. Interviews began by asking the participants to describe their ASA incidents with follow-probes asking about the victimization, perpetrator characteristics (gender and relationship to participant), and context of assault (role of alcohol or drugs and setting). Participants were also asked if they discussed the assault with anyone and their reasons for disclosure or non-disclosure. As well as short and long-term coping patterns. The daily survey asked participants about their mood, alcohol use, drinking contexts, and sexual experiences (consensual and non-consensual). This study contains demographic information such as: age, race, income, education, and BMI.

Global Crime Trends: An In-Depth Analysis of India's Crime Growth (1970-2020)

Crime rates have seen a significant and concerning rise across the globe, with India being no exception. This dataset provides a comprehensive overview of crime growth in India from 1970 to 2020, highlighting the alarming increase in both registered and unregistered cases.

The dataset meticulously details various types of violations, including sexual assaults, offering valuable insights into the nature and extent of crimes over the past five decades. By examining this data, one can better understand the broader implications these trends have had on society, both within India and globally. This dataset serves as a crucial resource for researchers, policymakers, and analysts seeking to explore the factors driving this increase in crime, its impact on communities, and potential solutions to address these issues.

Key Information about the dataset

Here's a summary of the CSV files you have:

1. Summary of Cases (Rape) 2015-2020:

   • Description: This file provides a year-wise summary of reported rape cases across various States and Union Territories in India from 2015 to 2020.
   • Columns: State/UT, Number of Cases Reported (CR) for each year from 2015 to 2020.

2. Detailed Cases (Registered) Sexual Assault 2001-2008:

   • Description: This dataset offers detailed information on registered sexual assault cases between 2001 and 2008, including both incest and non-incest rape cases. It categorizes the number of cases and victims by age group.
   • Columns: State/UT/City, Year, Number of Cases Reported, Number of Victims categorized by age group, and total figures for both incest and other rape cases.

3. Cases (Oldest) 1970:

   • Description: A historical dataset from 1970, providing details on various commodities, including stock levels, across different districts.
   • Columns: Date, Code, Commodity ID, Commodity Name, District Name, District Code, Stock, Commodity Stock, Total Stock.

4. Worldwide Cases Details:

   • Description: This dataset includes global crime data, with information on various indicators across different countries and regions, categorized by sex and age.
   • Columns: Country (ISO3 code), Region, Subregion, Indicator, Dimension, Category, Sex, Age, Year, Unit of Measurement, Value, Source.

5. Detailed Registered and Unregistered Cases (Sexual Assault) (Punished Release) 2018:

   • Description: This dataset details both registered and unregistered sexual assault cases from 2018, with a focus on custodial and non-custodial rape cases, including specific punishments.
   • Columns: State/UT, Year, various custodial and non-custodial rape categories, punishment details, and total cases.

6. State-wise Sexual Assault (Detailed) 1999-2013:

   • Description: This dataset provides a detailed state-wise account of sexual assault cases from 1999 to 2013, focusing on the relationship between the victim and the offender.
   • Columns: State/UT, Year, Number of Cases by Offender Relationship (e.g., parents, relatives, neighbors, other known persons).

These files collectively provide a comprehensive view of the crime trends, especially sexual assaults, across different periods and regions, both within India and globally.

Here's a table summarizing the years covered in each CSV file:

Source Open Government Data (OGD) Platform India | data.gov.in and crime-violent-offences | dataUNODC dataunodc.un.org

Used - ChatGPT for detailed information (CrossVerified)

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 project set out to understand the specific contributions Alaska's village public safety officers (VPSOs) make to the criminal justice responses to violence committed against Alaska Native and American Indian women in Alaska's tribal communities. More specifically, the goal of this study was to empirically document and assess the impact Alaska's VPSO program has on the investigation and prosecution of those who commit acts of sexual and domestic violence against Alaska Native and American Indian women in Alaska's tribal communities. The data collected for this study were compiled from detailed case record reviews of a random sample of sexual assault, sexual abuse of a minor, and domestic violence incidents investigated by the Alaska State Troopers (AST) and closed between January 1, 2008 and December 31, 2011. Data pertaining to case-level (e.g., year and month of incident report and case closure, time to report) and incident-level (e.g., assault location, weapon use, assaultive behaviors) characteristics were collected, as were demographic data describing suspects, victims, and witnesses/third parties. The study also collected data detailing suspect and victim alcohol/drug use and intoxication, injuries sustained by victims, victim resistance strategies and behaviors, and victim disclosures, among other measures. Additional charging and case resolution (referral, prosecution, conviction) data were also compiled. Finally, the study collected detailed data on the activities and roles played by VPSOs in investigations, as well as additional follow-up activities and services provided to victims. In total, 683 sexual assault (SA) and sexual abuse of a minor (SAM) and 982 domestic violence (DV) case records were coded and analyzed. The study collections includes 6 Stata (.dta) files. The zip file includes 2013-VW-CX-0001_DV_CASE.dta (n=982; 127 variables), 2013-VW-CX-0001_DV_CHARGE.dta (n=3711; 23 variables), 2013-VW-CX-0001_DV_INDIV.dta (n=3747; 105 variables), 2013-VW-CX-0001_SA_CASE.dta (n=683; 133 variables), 2013-VW-CX-0001_SA_CHARGE.dta (n=1060; 24 variables), 2013-VW-CX-0001_SA_INDIV.dta (n=3140; 112 variables).

In present times, gender-based violence (GBV) is a global scourge. It is highly prevalent in South Africa, where the rates of incidents are exorbitant, particularly those of sexual violence against women. The goal of this paper is to explore the implications of factors such as societal norms affected by the country’s unique historical circumstances that promote rising rates of gender-based violence, significant underreporting of these instances, sexual violence and the consequences for the survivors. The paper uses secondary data to study the intersectionality of gender, population group (race), socio-economic status, and geographical location. We further analyze the sociodemographic of GBV (particularly rape) victims and perpetrators to put the focus on better and more gender-responsive prevention strategies. The paper highlights the importance of paying attention to intimate partner violence (IPV) as this constitutes a highly significant percentage of the total cases of rape and femicide. The study shows that non-white women constitute the most vulnerable group to GBV. We conclude that proper mechanisms must be put in place which require the cooperation of the police, judicial, medical, social and other support services to properly tackle this violence which must account for every population group, especially the historically marginalized ones.Citation: Alvarez Merino, E., & Afa, I. J. (2025). Exploring the Complexities of Gender-Based Violence in South Africa: A Comprehensive Analysis. International Journal of Humanities and Social Science, 15, 26-38. https://doi.org/10.1080/ijhss.v15p3URL: https://ijhssnet.com/journal/index/5011

This dataset is from the SAFE study, focusing on developing and evaluating an eHealth intervention for women in the Netherlands who experience intimate partner violence and abuse (IPVA). The first goal was to assess needs, wishes and obstacles with regard to an eHealth intervention in the context of IPVA and to develop an eHealth intervention for women who experience IPVA. This, together with scientific literature and similar interventions in the IPVA context, inspired the content and functionalities of the SAFE intervention. Then, we aimed for the intervention to increase self-efficacy, awareness and perceived support and to decrease anxiety and depression symptoms amongst its users: women (18-50 years old) who experience IPVA. Also, we aimed for the intervention to encourage women in help seeking, and that the intervention would be a suitable tool to deliver information and support its users.For the development phase, we interviewed women IPVA victims/survivors (18+) and professionals in the field of domestic violence and abuse (DVA) and IPVA (N=16; published study: https://journals.sagepub.com/doi/10.1177/08862605211036108). The eHealth intervention SAFE was launched in April 2019 and simultaneously gathering data for the RCT and process evaluation, aimed at evaluating the intervention, started. For the RCT, after the participant gave their consent (digitally), we followed women (18-50 years old) for 6 or 12 months (depending on when they were included; see protocol article for more info: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-08743-0) and gathered data on multiple timepoints: baseline (M0/T0, at registration; N=198), 3 months (M3/T1), 6 months (M6/T2), and 12 months (M12/T3). The RCT study had two study arms: control group and intervention group. With the intervention group receiving a more elaborate and interactive intervention than the control group (see protocol article for additional information on the content of the intervention). All RCT data was gathered online, with questionnaires on demographic data, on their IPVA experience, and with the primary outcome being self-efficacy at M6 (measured with the General Self-Efficacy Scale (GSE)). Examples of secondary outcomes are anxiety and depression (measured with the Hospital Anxiety and Depression Scale (HADS)). The process evaluation included quantitative and qualitative data. Quantitative from the Web Evaluation Questionnaire (WEQ) that assessed how users graded the intervention, if they felt it was safe and easy to use etc. WEQ data was gathered at one month after the first login (M1), 3 months (M3) and 6 months (M6) after registering for SAFE. The qualitative data consists of interviews with participants from the RCT intervention study arm: N=10. The semi-structured interviews focused on the users' experiences with and opinions on the SAFE eHealth intervention.Data are in Dutch. Two sets of interview data: one from the development phase and one from the process evaluation. Two Excel documents with the final codebooks for the two interview studies. Two SPSS datasets for the RCT and process evaluation. Data are anonymized and pseudonymized to ensure the participants' safety and privacy. All participants provided (digital) informed consent before participating.- Interview data development phase (with survivors / victims and professionals): gathered in 2018, in person interviews, N=16. Publication: https://journals.sagepub.com/doi/10.1177/08862605211036108- Interview data process evaluation (with participants from the RCT intervention study arm): gathered in 2021, online interviews, N=10. No publication yet.- SPSS data RCT (with a control and intervention study arm): gathered in 2019-2021, via online questionnaires (e.g. demographic data, General Self-Efficacy Scale, Hospital Anxiety and Depression Scale, Bem Sex Role Inventory, Medical Outcomes Study Social Support 5), N=198 at baseline. No publication yet. Protocol: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-08743-0- SPSS data process evaluation: gathered in 2019-2021, via online questionnaire (Web evaluation questionnaire). No publication yet. Protocol: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-020-08743-0Methodology interview data: semi-structured interviews, open thematic coding in Atlas.ti, with 2 or 3 researchers coding independently, qualitative content analysis, grounded theory.Methodology questionnaire data: use of validated questionnaires, analyzing in SPSS: descriptive statistics, check for selective attrition bias, T-tests, ANCOVA, GEE. Data from the development process (interviews), RCT and process evaluation

A qualitative research methodology was utilised to seek an in-depth understanding of students’ lived experiences of gender-based violence (GBV) at a South African University. This study investigated the experiences of students who were victims of GBV at a South African university. Through carefully and thoroughly planned interviews, this was achieved by exploring the experiences of three students who have previously experienced gender-based violence. The conclusions drawn in the study emanate from the interviews conducted with the participants as well as the literature that informed the study. The three students employed in the study were all women. The first step of the data analysis included familiarizing myself with the raw data obtained from the interviews in the form of transcriptions. Additionally, codes were generated using the participants' exact statements from the transcripts. Secondly, data was organised and grouped together with the aim of searching for themes. Lastly, themes were reviewed, finalised, and named.

The findings in the dataset suggested that the participants tend to be weary of people on campus rather than the campuses themselves, or the surrounding areas such as the residences or public areas. Their main concern revolved around the perception that men are the catalysts of instilling the fear of potential harm within various contexts, and the university spaces being one of them. Undoubtedly, the female students’ activities and daily experiences appear to be cultivated and constrained by the fear of sexual violence, harassment, and emotional harm. In summary, the findings in the dataset highlighted that the students were keenly aware of the GBV prevalence on university campuses and surrounding spaces, which birthed an innate fear of potential harm within these spaces. Furthermore, the students each shared the experience of feeling that the university could do more to disperse widespread awareness and information about student safety protocols and legislation with regards to GBV incidences. Therefore, the findings of this study do provide evidence that GBV in the university environments may need to be further examined and that more should be done to ensure that students are safeguarded by university policies and laws.

Additional file 1. Study questionnaire.

Victim and perpetrator characteristics over the 3 surveys for IPF and NIPF: weighted and non-imputed data.