Meaningful Data Disaggregation for Gender Equality and Social Inclusion Outcomes

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Author(s):
Basanta Pokharel
Organization(s):
Institution(s):
Date Published:
December 6, 2017
Contribution:
Community Contribution

Nepal’s history of conflict and its disparities in human development outcomes among different castes, ethnic groups, and gender identities are rooted in discrimination and inequality. Taking this into account, all USAID projects aim to integrate gender equality and social inclusion (GESI) into their approaches and objectives. GESI is a concept that addresses unequal power relations between women and men and between different social groups.

Since GESI is central to the effective implementation of the project, Sajhedari Bikaas employed the CLA approach with members of both the prime and sub partners to intentionally collect, analyze, and use data to effectively advance GESI through the project’s interventions. Following a review finding that identified the need to use disaggregated data more intentionally, we decided to use this existing collaboration platform to effectively use data to collaborate, learn, and adapt our approaches to GESI integration on a regular basis.

The CLA approach has benefitted the project on multiple levels. On one hand, Sajhedari Bikaas is better able to present more nuanced reports on how inclusive, or not, our efforts have been over time. At the same time, there has been a gradual building of capacity of the team to understand the importance and use of disaggregated data to advance GESI considerations in our project.

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