Apr 16, 2026  |  Berkeley, CA

BITSS Annual Meeting 2026

The BITSS Annual Meeting brings together actors from academia, scholarly publishing, and policy to share novel research and discuss efforts to improve the credibility of social science by advancing research transparency, reproducibility, rigor, and ethics. The 14th BITSS Annual Meeting took place on Thursday, April 16th at the UC Berkeley Haas School of Business. BITSS and the Institute for Business and Social Impact (IBSI) co-hosted the event.

The agenda featured a morning session “Frontiers on AI and Open Science”. The BITSS community has been exploring how LLM applications can improve evidence synthesis and workflows. Reach out to the BITSS Program Manager with questions about the event and/or any of the presentations!

 

Presentations

Rigor, Transparency, and Replicability in NIH-funded Biomedical Research | Devon Crawford, NIH/NINDS Program Director

AI Forecasting for Social Science | Eva Vivalt, University of Toronto

Mining Meaning: Conducting AI-Assisted Reviews of Economic Literature | Kieran Douglas, UC Davis

Evidence Aggregation: Extracting Metadata from RCTs at Scale | Sergio Puerto, BITSS

Replicating Lab Experiments with LLM Simulations | Jacob Snyder (NBER/UC Berkeley) and Abhishek Nagaraj (NBER/UC Berkeley)

Tracking Data Quality in Online and Laboratory Pools | Don Moore, UC Berkeley Haas School of Business

Mass Reproducibility and Replicability: Methods and Fields | Derek Mikola, Institute for Replication (I4R), University of Ottawa

When is p-hacking detectable? | Stefan Faridani, Georgia Institute of Technology

Beyond Publication Bias: Characterizing and Understanding Missing Results in Economics | Fernando Hoces De La Guardia, BITSS

Balancing Data Privacy and Research Transparency: the IP4OS Toolbox | Katharina Miller, IP4OS