Intelligent research design for data intensive social science
Who we serve D-Lab helps UC Berkeley undergraduate students, graduate students, faculty, and staff move forward with world-class research in data intensive social science and humanities.
What we do D-Lab assists the Berkeley community with the full range of research development, research design and data acquisition. We offer guidance in statistical methods and results to data visualization and communication.
Who we are D-Lab is comprised of scholars who create a learning community that teaches workshops and offers consultations. Join us!
by Nanqin Ying. This study analyzes over 50 million judicial decisions from China’s Supreme People’s Court to examine disparities in legal representation and their impact on sentencing across provinces. Focusing on 290 000 drug-related cases, it employs large language models to differentiate...Read more about Leveraging Large Language Models for Analyzing Judicial Disparities in China
by Elaine Luo. As youth navigate an increasingly ethnoracially diverse society like the United States, their ethnic-racial identity (ERI) plays a crucial role in shaping various aspects of their development, including academic and psychosocial outcomes. In this post, I share insights from our...Read more about Understanding Adolescent Ethnic-Racial Identity: A Latent Profile Approach
by Ruiji Sun. We demonstrate the importance of causal thinking by comparing two linear regression approaches used in thermal comfort research: Approach (a), which regresses thermal sensation votes (y-axis) on indoor temperature (x-axis); Approach (b), which does the reverse, regressing indoor...Read more about Causal Thinking in Thermal Comfort
by Yue Lin. What are the key challenges and opportunities of applying experiments in the International Political Economy (IPE) research? In this blog, I reviewed an enduring methodological battle between statistics and experiments, and pointed out that the difficulties of randomization and locating...Read more about Causal Inference in International Political Economy: Hurdles and Advancements
