May 19, 2026 – May 21, 2026 |

Research Transparency and Reproducibility Training (RT2) 2026

About RT2

The Berkeley Initiative for Transparency in the Social Sciences (BITSS) held a Research Transparency and Reproducibility Training (RT2) in Berkeley, CA on May 19 – 21, 2026. RT2 provides participants with an overview of tools and best practices for transparent and reproducible social science research. The curriculum was developed and delivered by academic leaders in the open science movement as well as experts on aging and health disparities. The three-day training included space for collaborative work and hands-on skill building, with participant presentations on their research questions and ideas.

RT2 2026 Participants I Photo: Indira Cummings, CEGA

Curriculum

The RT2 training included the following presentations:

The Scientific Ethos, Misconduct, and Transparency by Edward Miguel (UC Berkeley; BITSS Faculty Director; CEGA Faculty Co-Director)
The Role of Journals in Advancing Transparency by Simine Vazire (University of Melbourne)
Power Calculations by Michael Walker (UC Berkeley)
Conducting Reproducible Research with AI by Sergio Puerto (UC Berkeley)
Mastering Version Control with GitHub by Akash Shaji (UC Berkeley)
Pre-Registration for Quasi-Experimental Data by Thomas Dee (Stanford University)
Lessons from the Medical Field: Pre-Analysis Plans and Peer Review by Jade Benjamin Chung (Stanford University)
Data Management: Conducting Responsible, Reproducible Research by Sam Teplitzky (UC Berkeley)
Reproducible Workflows in R and Stata by Gufran Pathan (UC Berkeley)
Gateway to Global Aging Data: Introduction and Using the Platform by Drystan Phillips (USC)
Lessons on Pre-Registrations and Pre-analysis Plans by Fernando Hoces (UC Berkeley)

Eligibility

RT2 is designed for researchers in the social and health sciences, with particular emphasis on economics, political science, psychology, and public health. Participants are typically (i) current Masters and PhD students, (ii) postdocs, (iii) junior faculty, (iv) research staff, (v) librarians and data stewards, and (vi) journal editors, funders, and research managers curious about the implications of transparency and reproducibility for their work. The RT2 curriculum is most applicable to researchers who use quantitative or mixed methods. Applicants should have proficiency in R or Stata.

Selection Process

BITSS aims to select no more than 40 participants for RT2. As the number of applications for RT2 tends to exceed the number of available spaces, we will competitively select participants based on (i) the quality of application materials and expected impact and (ii) balance across disciplines, gender, and institutions. BITSS staff will lead the selection process with oversight from the BITSS Faculty Director.