Social Justice

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.

Data Science for Social Justice 2024 (Apply by April 15)

March 15, 2024, 12:00pm
This 8-week workshop will give you the opportunity to learn the essential tools and methods for data science analysis and be introduced to critical frameworks that will enable you to create a project of your own design and to tell stories that can counter the market-first mentality of data science. This workshop has a heavy emphasis on collaboration and peer-to-peer learning, with a significant group work component.

Data Science + Social Justice Workshop (Apply by May 1)

May 1, 2022, 10:00am
This 6-week workshop will give you the opportunity to learn the essential tools and methods for data science analysis and be introduced to critical frameworks that will enable you to create a project of your own design and to tell stories that can counter the market-first mentality of data science.

Data Science for Social Justice Workshop 2023

March 1, 2023, 12:00pm
This 8-week online workshop for currently enrolled UC Berkeley graduate students will give you the opportunity to learn the essential tools and methods for data science analysis and be introduced to critical frameworks that will enable you to create a project of your own design and to tell stories that can counter the market-first mentality of data science.

Sand Mining - Plugging a Critical Data Gap

May 14, 2024
Suraj Nair
by Suraj Nair. Excessive sand mining is causing a global ecological crisis. In this blog post, I present why sand mining is one of the most pressing challenges facing the planet, and why persistent data gaps hinder accountability and monitoring. I also discuss an ongoing research project of mine where we combine freely available satellite imagery and machine learning models to build open-source sand mine detection tools that can plug some of these data gaps.

The More Things Change the More They Stay the Same?

December 18, 2023
Tonya Lindsey, Ph.D.
By Tonya D. Lindsey, Ph.D. Think about how often you hear someone gripe about the deterioration of society and then blame the Internet or social media. This blog suggests that the things we are exposed to virtually are not new but instead present us with more and frequent opportunities to reflect on perennial social problems and find solutions even as we better understand ourselves as individuals in a global community.

Exploratory Data Analysis in Social Science Research

November 14, 2023
Kamya Yadav
by Kamya Yadav. Causal inference has become the dominant endeavor for many political scientists, often at the expense of good research questions and theory building. Returning to descriptive inference – the process of describing the world as it exists – can help formulate research questions worth asking and theory that is grounded in reality. Exploratory data analysis is one method of conducting descriptive inference. It can help social science researchers find empirical patterns and puzzles that motivate their research questions, test correlations between variables, and engage with the existing literature on a topic. In this blog post, I walk through results from exploratory data analysis I conducted for my dissertation project on political ambition of women.

Artificial Intelligence and the Mental Health Space: Current Failures and Future Directions

October 31, 2023
María Martín López
by María Martín López. María Martín López, a PhD student in the department of psychology whose research focuses on large language models within the context of mental illness, gives an overview of current failures and possible future directions of NLP models in the mental health space. She brings up questions that must be considered by all researchers working in this space and encourages these individuals to think creatively about the use of AI beyond direct treatment.

Americanist Linguistics: on Ethics and Intent

October 17, 2023
Anna Bjorklund
by Anna Björklund. In this post, Anna Björklund investigates the origin of the linguistic study of indigenous American languages, its inextricable ties to settler-colonialism, and how linguistics can move forward as a field.

Critical Faculty and Peer Instructor Development: Core Components for Building Inclusive STEM Programs in Higher Education

Claudia von Vacano, Ph.D.
Michael Ruiz
Renee Starowicz, Ph.D.
Seyi Olojo
Arlyn Y. Moreno Luna
Evan Muzzall, Ph.D.
Rodolfo Mendoza-Denton, Ph.D.
David Harding, Ph.D.
2022

First-generation college students and those from ethnic groups such as African Americans, Latinx, Native Americans, or Indigenous Peoples in the United States are less likely to pursue STEM-related professions. How might we develop conceptual and methodological approaches to understand instructional differences between various undergraduate STEM programs that contribute to racial and social class disparities in psychological indicators of academic success such as learning orientations and engagement? Within social psychology, research has focused mainly on student-level mechanisms...