Abstract

Data intersectionality, based on the concept of intersectionality, is an approach to data and data analysis that offers a better understanding of how multiple social identities interact and influence a person's experiences and outcomes. It highlights disparities that may be otherwise hidden or obscured when only looking at single dimensions of identity. Intersectional data lies at the heart of inclusive development efforts, and this approach has become increasingly recognized as fundamental in reaching the most marginalized populations. Despite the importance, the availability and use of intersectional data, especially for persons with disabilities, remain limited, posing significant challenges to evidence-based and inclusive decision-making in many countries. Thus, this presentation will highlight the role of intersectional data in the data value chain to better understand persons with disabilities as key actors in generating and using disability data to ensure inclusive policies and programs. Case studies from Ecuador, Mongolia, and the Philippines will provide practical examples of how marginalized communities, in this case, disability and deaf communities, can collect, use, and control their own data to influence policy change.