BITSS funds and conducts meta-research, and supports the development of new tools and methods for research transparency and reproducibility.
We produce research that tackles two key problems:
- Limited understanding of the state of stakeholder norms and practices
An ever-growing body of literature shows evidence for the negative consequences of poor research transparency (publication bias, p-hacking, errors, and fraud). However, there is also a limited understanding of current norms and practices related to research transparency, as well as the challenges in the adoption of methods and tools for research transparency.
- Limited supply of and evidence for solutions to improve research transparency and reproducibility
While the research transparency community generally agrees that publishing a pre-analysis plan is an important first step to mitigating researcher degrees of freedom like p-hacking, there is limited consensus on what a pre-analysis plan should include in order to maximize research quality. Moreover, there are a variety of potential solutions, incentives, and policies that can and should be tested to assess what works and what doesn’t to change norms and practices.
Forecasting Social Science Results
Led by Stefano DellaVigna (UC Berkeley) and Eva Vivalt (Australian National University), BITSS is supporting the development of the Social Science Prediction Platform (currently in beta), where researchers can systematically collect, catalog, and access forecasts. Learn more here.
Social Science Meta-Analysis and Research Transparency (SSMART) Grants
The SSMART grant program aims to improve the quality of research in economics, political science, psychology, and related social science disciplines by funding meta-scientific studies and research related to transparency and reproducibility issues. Browse research supported through the SSMART program here.
Research led by BITSS scientific staff and research partners generates transparent and reproducible evidence for problems in social science research and solutions to these problems. Our work has produced data and evidence on researcher attitudes, norms, and behaviors. Browse BITSS research here.
Managed by BITSS, MetaArXiv is an interdisciplinary and open access archive of articles focused on meta-science and improving research transparency and reproducibility. The archive includes working papers, pre-prints, post-prints, and other scholarly works like dissertations, reports, statistical software package tutorials, and conference proceedings.
Data Publication Grants
To facilitate transparency and future replications, BITSS provided small grants for the preparation of datasets, codebooks, analysis code, and other study materials for public release. Browse supported projects here.