Blog post

Human-Centered Design for Migrant Rights

October 29, 2024
Victoria Hollingshead
by Victoria Hollingshead. In honor of the 2024 International Day of Care and Support, Victoria Hollingshead shares her recent work with the Center for Migrant Advocacy’s Direct Assistance Program and their innovative approach to supporting Overseas Filipino Workers (OFWs) using generative AI. OFWs, especially female domestic workers in the Gulf Cooperation Council (GCC), are vulnerable to exploitation from foreign employers and recruitment agencies while having limited access to legal support. Using a design thinking framework, Victoria and CMA’s Direct Assistance team co-designed a proof of concept to enhance the legal and contract literacy among OFWs in the Kingdom of Saudi Arabia, a top destination country. This project shows promise in leveraging emerging technologies to empower OFWs, enhancing the Philippines' reputation as a migrant champion and supporting the nation's broader push for digital transformation.

Concepts and Measurements in Social Network Analysis

October 22, 2024
Christian Caballero
by Christian Caballero. We live in an interconnected world, more so now than ever. Social Network Analysis (SNA) provides a toolkit to study the influence of this interconnectivity. This blog post introduces some key theoretical concepts behind SNA, as well as a family of metrics for measuring influence in a network, known as centrality. These concepts and measurements help form the basis for a theoretically informed study of social relationships in an era where the availability of relational data has dramatically increased thanks to technological advances.

The Case for Including Disability in Social Science Demographics

October 15, 2024
Jane (Mango) Angar
by Mango Jane Angar. As we celebrate Disability Awareness Month at the D-Lab alongside the UC Berkeley scholarly community, how can we, as social scientists, individually promote accessibility and inclusion? To advance accessibility, we should focus on addressing the barriers faced by individuals with disabilities, using our research to provide insights for effective policy recommendations. Although most of us do not focus on disability-related issues, including disability as a demographic characteristic in our data collection can greatly enhance our understanding of diverse populations and improve the comprehensiveness of our analyses. This small step can contribute to broader efforts toward inclusion and social equity.

Leveraging Large Language Models for Analyzing Judicial Disparities in China

October 8, 2024
Nanqin Ying
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 between private attorneys and public defenders and assess their sentencing outcomes. The methodology combines advanced text processing with statistical analysis, using clustering to categorize cases by province and representation, and regression models to isolate the effect of legal representation from factors like drug quantity and regional policies. Findings reveal significant regional disparities in legal access driven by economic conditions, highlighting the need for reforms in China’s legal aid system to ensure equitable representation for marginalized groups and promote transparent judicial data for systemic improvements.

Consulting: Supercharge Your Research with Hugging Face’s Toolkit

October 1, 2024
Iñigo Parra
Supercharge Your Research with Hugging Face’s Toolkit

Are you looking to elevate your research projects with cutting-edge machine learning models? Hugging Face might be just the tool you need. This platform makes it easy to access and implement state-of-the-art models, bringing efficiency and innovation to your work like never before.

Hugging Face is highly user-friendly, even for those new to Python or machine learning. It hosts thousands of models, offering diverse tools from natural language processing and computer...

Understanding Adolescent Ethnic-Racial Identity: A Latent Profile Approach

September 24, 2024
Elaine (Hua) Luo
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 recent study on adolescent ERI and youth adjustment. Using a person-centered approach, we identified four distinct ERI profiles: Strongly Diffused, Moderately Diffused, Balanced, and Achieved. Our findings revealed differences in educational motivation, school belonging, and expectations for discrimination across these profiles, highlighting the complexity of ERI development. Implications for caregivers, educators, and communities are also discussed.

Causal Thinking in Thermal Comfort

September 17, 2024
Ruiji Sun
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 temperature (y-axis) on thermal sensation votes (x-axis). From a correlational perspective, they may appear interchangeable, but causal thinking reveals substantial and practical differences between them. Using the same data, we found Approach (b) leads to a 10 °C narrower than the conventionally derived comfort zone using Approach (a). This finding has important implications for occupant comfort and building energy efficiency. We highlight the importance of integrating causal thinking into correlation-based statistical methods, especially given the increasing volume of data in the built environment.

Causal Inference in International Political Economy: Hurdles and Advancements

September 9, 2024
Yue Lin
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 credible counterfactuals have served as main hurdles for IPE scholars to widely adopt experimental tools. However, I further demonstrated some new progress in applying survey, field, and lab experiments in the recent IPE scholarship. I concluded that it is crucial for future researchers to think innovatively about how to combine different research methods to make causal claims in IPE studies.

Data for a Just U.S. - Using Data Science to Empower Marginalized Communities

September 3, 2024
Elijah Mercer
by Elijah Mercer. In this blog post, I share how working with marginalized communities through data science has transformed my understanding of the field. My journey from crime analysis to founding Data for Just US reveals the profound impact data can have when used to empower and uplift underserved populations. I explore the challenges and rewards of this work, illustrating how data science can drive social change and foster a more equitable future.

Minding the Gaps: Pay Equity in California

July 9, 2024
Tonya D. Lindsey, Ph.D.
by Tonya D. Lindsey, Ph.D. The gender pay gap continues to reflect that, on average, men outearn women. California is among the states with the smallest pay gaps (outpacing the national number at 13%) and is unique in that it enacted legislation aimed at eliminating pay gaps by sex and race categories. This blog post reflects on California’s pay gap as students study it in an undergraduate social statistics course. Independent variables indicate three theoretical frameworks: 1) human capital, 2) occupational segregation, and 3) discrimination. While the work students do is rigorous using a representative sample of full-time year-round California workers, there remains work to be done and caveats to the data and analyses.