DSAI Cohorts

by Taesoo Song. Asian Americans are often overlooked in discussions of racial inequality due to their high average socioeconomic attainment. Many academic and policy researchers treat Asians as a single racial category in their analysis. However, this broad categorization can mask significant within-group disparities, leaving many disadvantaged individuals without access to vital resources and policy support. Song emphasizes the importance of data disaggregation in revealing Asian American inequalities, particularly in areas like income and homeownership, and demonstrates how breaking down these categories can lead to more targeted and effective policy solutions.

by Elijah Mercer. Data literacy is a powerful tool for empowerment, especially for historically marginalized communities. Through Data Cafecito at Roadmap to Peace and helping teach Data 4AC at UC Berkeley, Elijah Mercer helps bridge the gap between data, advocacy, and justice. Data Cafecito fosters culturally responsive data practices for Latinx-serving organizations, while Data 4AC challenges students to critically analyze data’s role in systemic inequities. Drawing from his experience in education, Mercer uses interactive teaching methods to make data accessible and meaningful. By centering storytelling and community-driven insights, he aims to equip individuals with the skills to use data for social change.

by Ruiji Sun. We introduce and apply regression discontinuity to thermal comfort field studies, which are typically observational. The method utilizes policy thresholds in China, where the winter district heating policy is based on cities' geographical locations relative to the Huai River. Using the regression discontinuity method, we quantify the causal effects of the experiment treatment (district heating) on the physical indoor environments and subjective responses of building occupants. In contrast, using conventional correlational analysis, we demonstrate that the correlation between indoor operative temperature and thermal sensation votes does not accurately reflect the causal relationship between the two. This highlights the importance of causal inference methods in thermal comfort field studies and other observational studies in building science where the regression discontinuity method might apply.