Monica De La Cruz

FOCUS
Monica’s research interest focuses on ways to ameliorate family poverty as a means to positively impact children’s health, specifically for communities of color. Children living in poverty are at risk for a multitude of negative outcomes in health and safety, school success and educational attainment, and adult earning potential and productivity. Disproportionate poverty in communities of color is the result of systemic racism and inequity that cannot be reversed through local interventions alone. Monica aims to translate her research into policies that help dismantle these systems and shift the national discourse on family poverty to one that is both racially just and centers subsistence as a human right for all.

MORE ABOUT MONICA
Monica has extensive experience conducting qualitative, community-based, and community-driven participatory research. Prior to graduate school, Monica worked on an interdisciplinary team at the Stanford School of Medicine examining the impact of local interventions on addressing basic needs insecurity (food insecurity, diaper insecurity).

DISSERTATION GRANT AWARDEE — FALL 2022
Beyond Sticks and Stones: Exploring Discourses of Poverty

Discourses and narratives of poverty are often stigmatizing and rooted in racism, sexism, and the deep-seated American beliefs of meritocracy and individualism. These narratives are internalized and reproduced throughout society to impact the real lived experiences of people, especially those in poverty. This dissertation aims to 1) explore qualitatively through in-depth interviews if and how the narratives within discourses of poverty have impacted people who have sought public assistance; 2) explore, quantitatively, if and how the narratives within discourses of poverty are related to whether people support or oppose guaranteed income as a poverty solution through a nationally representative survey; and 3) explore if and how the narratives within discourses of poverty are reflected in the discussions about guaranteed income, specifically in online discourse, using natural language processing, a machine learning method.

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