Banyan Global is implementing the Gender Integration Technical Assistance (GITA) task order under the Advancing the Agenda of Gender Equality (ADVANTAGE) indefinite delivery, indefinite quantity contract. GITA provides on-demand, rapid response short-term technical assistance (STTA) to the United States Agency for International Development (USAID) Missions and Bureaus across sectors.
Under GITA, Banyan Global carried out a gender and social inclusion (GESI) analysis for USAID/Rwanda from April to August 2019 to inform the Mission’s FY 2019-2024 Country Development and Cooperation Strategy (CDCS). Using Banyan Global’s tested gender and social inclusion analysis research tools, the three-person research team identified systemic advances, gaps, and opportunities across thematic areas in Rwanda. The goal of USAID/Rwanda’s country level gender analysis was to identify the macro-level gender and social inclusion issues, inequalities, constraints, and opportunities, and provide specific recommendations on how USAID can achieve greater integration of marginalized populations in its strategic planning in four key sectors: health and nutrition, education, democracy and governance, and economic empowerment and growth.
The research team worked in close collaboration with Mission staff to identify best practice gender and social inclusion research approaches and provide support to integrate key findings into their CDCS process. The GESI analysis summarizes findings and recommendations related to: issues and challenges affecting access to health, education, agriculture and economic growth, and democracy and governance for women, persons with disabilities, or people who are LGBTI; promising practices that have addressed the needs of women, persons with disabilities, or people who are LGBTI; different impacts of interconnected issues, such as nutrition, gender-based violence (GBV), youth concerns, and civic participation; and mechanisms, platforms, and opportunities for addressing gaps, knowledge sharing, and innovations to be applied in future programming.