Qualitative Analysis

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.

US Census Bureau Restricted-Access Research Data Center (FSRDC) Info Session

April 24, 2024, 11:00am
Interested in restricted Census or partnering RDC agency (AHRQ, BLS, BEA, NCHS) data use? This one-hour introductory workshop will provide an overview of the Berkeley Federal Statistical Research Data Center, with no prior experience assumed. Attendees will learn about the national RDC network, how to access information online about restricted Census data, and how to navigate proposal development.

QDA Campus License Focus Group

October 12, 2023, 12:00pm
Calling All Qualitative & Mixed-Methods Researchers at UC Berkeley! Join the conversation on Qualitative Data Analysis (QDA) Campus Software License Options! Are you a researcher (undergraduate, graduate, or faculty/staff) at UC Berkeley who employs qualitative data, text analysis, or mixed-methods research approaches? If you rely on specialized software like Atlas.ti, NVivo, MaxQDA, Dedoose, or Otter.ai in your work, Research IT & D-Lab want your input to inform the future of qualitative research supports at UC Berkeley.

Survey Fundamentals

April 11, 2024, 3:00pm
This two-hour workshop offers a comprehensive introduction to designing and conducting survey studies. Tailored for beginners, it provides clear, step-by-step guidance complemented by concise examples, practical considerations, and useful support materials. Participants will learn the entire process, from formulating a research question to creating, administering, and analyzing surveys, as well as interpreting results and communicating their findings.

Survey Fundamentals

February 21, 2024, 1:00pm
This two-hour workshop offers a comprehensive introduction to designing and conducting survey studies. Tailored for beginners, it provides clear, step-by-step guidance complemented by concise examples, practical considerations, and useful support materials. Participants will learn the entire process, from formulating a research question to creating, administering, and analyzing surveys, as well as interpreting results and communicating their findings.

Berkeley FSRDC Fundamentals

January 31, 2024, 11:00am
Interested in restricted Census or partnering RDC agency (AHRQ, BLS, BEA, NCHS) data use? This one-hour introductory workshop will provide an overview of the Berkeley Federal Statistical Research Data Center, with no prior experience assumed. Attendees will learn about the national RDC network, how to access information online about restricted Census data, and how to navigate proposal development.

Skyler Yumeng Chen

Data Science for Social Justice Fellow 2024
Haas School of Business

Skyler is a Ph.D. student in Behavioral Marketing at the Haas School of Business. Her research centers on consumer behavior and judgment and decision-making, with a keen interest in both experimental methods and data science techniques. She holds a B.A. in Economics and a B.S. in Data Science from New York University Shanghai.

Enhancing Research Transparency Inspired by Grounded Theory

April 30, 2024
Farnam Mohebi
by Farnam Mohebi. Grounded theory, a powerful tool for qualitative analysis, can enhance data science research by improving transparency and impact. Researchers can create a vivid record of their process by meticulously documenting the entire research journey, including the decisions they make and the corresponding rationale behind them, from initial data exploration to developing and refining theories. Embracing grounded theory principles, such as iterative coding and constant comparison, can help data scientists build robust, data-driven theories while ensuring transparency throughout the research process. This approach makes research more replicable and understandable and invites others to engage with the work, fostering collaboration and constructive critique, ultimately elevating the value and reach of their findings.

Conceptual Mirrors: Reflecting on LLMs' Interpretations of Ideas

April 23, 2024
María Martín López
by María Martín López. As large language models begin to engrain themselves in our daily lives we must leverage cognitive psychology to explore the understanding that these algorithms have of our world and the people they interact with. LLMs give us new insights into how conceptual representations are formed given the limitations of data modalities they have access to. Is language enough for these models to conceptualize the world? If so, what conceptualizations do they have of us?

Transparency in Experimental Political Science Research

April 9, 2024
Kamya Yadav
by Kamya Yadav. With the increase in studies with experiments in political science research, there are concerns about research transparency, particularly around reporting results from studies that contradict or do not find evidence for proposed theories (commonly called “null results”). To encourage publication of results with null results, political scientists have turned to pre-registering their experiments, be it online survey experiments or large-scale experiments conducted in the field. What does pre-registration look like and how can it help during data analysis and publication?