WHO COUNTS? INVESTIGATING THE (IN)VISIBILITY OF NATIVE AMERICAN WOMEN WITH INTELLECTUAL AND DEVELOPMENTAL DISABILITIES IN HEALTH SURVEILLANCE
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PublisherThe University of Arizona.
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AbstractThe purpose of this study is to investigate the factors that shape the (in)visibility of Native American women with intellectual and developmental disabilities in health surveillance. This research is part of a larger project that aims to increase cancer screening rates among Native women with IDD. Previous research demonstrates that Native American women and women with disabilities receive cancer screenings less frequently than women in the general population—which suggests even greater screening disparities for Native women with IDD. However, data about the cancer screening rates of Native women with IDD, as well as basic demographic information such as the size of this population, do not exist. This paucity of health information limits the capacity for interventions that address the disparities experienced by these women, who exist at the intersection of several marginalized identities. To understand the forces that contribute to the limited demographic picture of Native women with IDD, I interviewed eleven experts who work with Native peoples and/or individuals with IDD in a variety of government, academic, and community settings. Drawing from participant interviews, I present three major barriers to the demographic visibility of this group of women. In Chapter One, I review the primary data systems in the United States, highlighting significant gaps in the demographic portrayal of Native women with IDD. In Chapter Two, I investigate the structural forces that limit Native women’s access to spaces of surveillance. In Chapter Three, I demonstrate how the Eurocentric epistemologies that guide data collection reinforce the demographic erasure of Native women with IDD by negating Indigenous worldviews. I conclude with a discussion of future directions, offering the paradigms of multivocality and Indigenous Data Sovereignty as a means to create a more equitable data landscape for intersectional populations such as Native women with IDD.