Oct 4, 2022  –  Dec 6, 2022

BITSS Open Research Seminar (Fall 2022)

The Berkeley Initiative for Transparency in the Social Sciences (BITSS) is excited to announce the Open Research Seminar (ORS), a webinar series to promote and share knowledge about the use of tools and practices for transparency and reproducibility in social science research. The ORS will be an opportunity for researchers to showcase applications of specific tools and practices (e.g., developing a lab protocol for reproducibility, building a website to catalog open datasets, etc.) or evaluations of the effectiveness of existing tools and practices (e.g., results-blind peer review and publication bias). All webinars will be free and open to register to the general public.

Register for the Fall 2022 ORS here!

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Feb 22, 2021  –  Feb 23, 2021

Panel: Open Science – Increasing Rigor, Reproducibility, Transparency, and Dissemination

Feb. 23, 2021 — BITSS Faculty Director Ted Miguel chaired a panel titled “Increasing Rigor, Reproducibility, Transparency, and Dissemination” as part of the Science of Behavior Change Capstone Conference organized by the National Institutes of Health Feb. 22-23, 2021. The panel featured the following presentations:

  • Reimagining science as truly open and inclusive, Alison Ledgerwood, University of California, Davis
  • An open science behavior change model from theory to practice, Brian Nosek, Center for Open Science
  • The art of open science: Imitation, inspiration, and innovation, Chaning Jang, The Busara Center for Behavioral Economics

See the program and find videos here.

Feb 22, 2021  –  May 14, 2021

Catalyst course: Improving (Our) Science — Replication, Reporting, and Openness

Don Moore and Leif Nelson (Haas School of Business, UC Berkeley) offer “Improving (Our) Science: Replication, Reporting, and Openness”, an online course that is open for registration to PhD students interested in open science. The goal of the course is to learn about the newest standards for scientific openness, and how they influence the reporting and interpretation of empirical evidence. Learn more in the course syllabus here.

Contact Don Moore to register.