Research Transparency Forum
The movement towards more transparency, reproducibility, and openness has gained a lot momentum in the social sciences. Yet, the norms and institutions that govern academic research do not reflect this culture shift. Significant problems remain, including professional incentives that reward striking and statistically significant research findings at the expense of scientific integrity.
Increasing the reliability and accuracy of scientific evidence requires well-defined standards of methodological rigor. At the same time, new tools and strategies to increase transparency must be integrated into existing research workflows to facilitate adoption. As the social sciences reinvent their practices around data, it is absolutely the right moment to build new channels of collaboration, cross-learning, and dissemination for innovative, open research practices.
The two-day conference brought together academic leaders, scholarly publishers, and policy-makers to discuss recent innovations in journal practices, academic training, data sharing, and evidence-based policy in light of the push for increased transparency.
The event was organized by BITSS in partnership with the Center for Effective Global Action, the Center for Open Science, D-Lab, The Berkeley Institute for Data Science, the Alfred P. Sloan Foundation, and the Laura and John Arnold Foundation.
Presentation slides are available for download on the Open Science Framework.
- John Ioannidis (Professor of Health Research and Policy at Stanford School of Medicine, and Co-Director of the Meta-Research Innovation Center)
- Edward Miguel (Professor of Economics at UC Berkeley, and Faculty Director of the Center for Effective Global Action)
- Jack Molyneaux (Director of Impact Evaluations at Millennium Challenge Corporation)
- Brian Nosek (Professor of Psychology at the University of Virginia, and Director of the Center for Open Science)
- Victoria Stodden (Professor of Statistics at the University of Illinois, and founder of ResearchCompendia, RunMyCode, and SparseLab)
- Neil Malhotra (Stanford University): “Publication Bias in the Social Sciences: Unlocking the File Drawer”
- Uri Simonsohn (University of Pennsylvania): “False-positive Economics”
- Maya Petersen (UC Berkeley): “Data-adaptive Pre-specification for Experimental and Observational data”
- Arthur Lupia (University of Michigan) and Colin Elman (Syracuse University): “Data Access, Research Transparency, and the Political Science Editors’ Joint Statement”
- Jan Höffler (University of Göttingen): “ReplicationWiki: A Tool to Assemble Information on Replications and Replicability of Published Research”
- Garret Christensen (BITSS): “A Manual of Best Practices for Transparent Research”