About 5.6 million Venezuelans have fled economic hardship and social unrest and are now refugees. Women and girls face gendered vulnerabilities such as intimate partner violence, sexual assault and harassment, as well as early unions, sexual exploitation, and survival sex in an effort to access basic goods and services.
Many gender-based violence (GBV) survivors suffer in silence due to feelings of shame and fear of repercussions, including deportation. A lack of knowledge about how and where to seek assistance, and the limited availability of gender-sensitive services, can impede survivors’ recovery.
Furthermore, sexual and reproductive health may be compromised due to sexually transmitted infections, and the lack of accessible contraception, pre-natal care, and family planning options.
Spryng.io sensemaking software is a mixed methods narrative capture application. The application asks individuals to share a brief story on a topic of interest (in this case the experiences of female refugees and migrants from Venezuela). The narrative is audio recorded and provides the qualitative data. Participants then interpret the experiences shared in their story by responding to a series of pre-determined questions on the tablet. These responses provide the quantitative data which is linked to the accompanying narratives to provide further insights and contextualization.
Queen’s University and IOM will use Spryng.io sensemaking software with 3,000 refugees and migrants from Venezuela, providing real-time, anonymous data on gendered experiences, including GBV risks related to sexual exploitation, IPV, survival sex, and trafficking, as well as capturing women’s perspectives on available services.
With efficient data collection and analysis, the project aims to learn whether GBV risks can be better identified and mitigated, and how the needs of survivors can be better met. Its data may also provide stakeholders with insightful information to strengthen GBV response and prevention strategies, as well as inform the design and implementation of responsive sexual and reproductive health (SRH) programming.
Queen’s University anticipates using Spryng.io to interpret the narratives of 3,000 refugees and migrants from Venezuela about GBV risks and experiences along their migration route. The team aims to identify actionable GBV threats for protection interventions, and to further SRH by improving access to and quality of care.
Through use of Spryng.io, the team will review weekly data and analyse patterns to identify early warning signs and newly identified GBV risks. Bi-weekly data reports will inform in-country GBV service providers. More broadly, regional GBV subsector members and other non-GBV actors will be able to utilise the collected data to inform their programming and services.
Queens University is using an innovative ‘sensemaking’ (SM) approach with Spryng.io software to identify issues of gender based violence and discrimination.View
The International Organization for Migration (IOM) and Queen’s University in Kingston (Canada) have been collaborating on a joint initiative to produce mixed-methods data regarding the GBV risks faced by Venezuelan women and girls. The project’s purpose was to improve the safety, well-being, and sexual and reproductive health of female Venezuelan refugees and migrants through more efficient data collection and analysis allowing for more responsive programming.View
For three years, IOM and Queen’s University have been collaborating on a joint research initiative with the objective of providing more efficient mixed-method data regarding the GBV risks faced by Venezuelan women/girls, including sexual assault, survival sex, and human trafficking.For three years, IOM and Queen’s University have been collaborating on a joint research initiative with the objective of providing more efficient mixed-method data regarding the GBV risks faced by Venezuelan women/girls, including sexual assault, survival sex, and human trafficking. The project’s purpose was to improve the safety, well-being, and sexual and reproductive health of female Venezuelan refugees/migrants through more efficient data collection and analysis, allowing for more responsive programming.View
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