Social, Behavioral Scientists Eligible to Apply for NSF S-STEM Grants
Solicitations are now being sought for the National Science Foundation’s Scholarships in Science, Technology, Engineering, and Mathematics program, and in an unheralded […]
We live in the information age. So where are all the answers? A new data science consortium led by NSF’s National Center for Science and Engineering Statistics wants to reveal the answers and evidence hidden in a sea of federally compartmentalized data.
According to NIST’s Reva Schwartz, bias manifests itself not only in artificial intelligence algorithms and the data used to train them, but also in the societal context in which AI systems are used.
Join the National Center for Science and Engineering Statistics and the Coleridge Initiative for a two-day conference to advance understanding of the […]
Being bad at math can kill people. Even experts who should understand medical science and help us make good health decisions sometimes […]
With economic, public health, and governance challenges arising from COVID-19 and political polarization, trustworthy public data is vital to open and honest […]
The Federal Committee on Statistical Methodology and Council of Professional Associations on Federal Statistics are hosting an eight-session webinar series on confidentiality […]
Angus Deaton called for the applied microeconomists not to abandon economic theory in favor of experiments but instead to think more deeply about the consequences of economic theories and how they can be tested using real-world data. This is the approach he has followed throughout his career and what has led to him win a Nobel Prize.
The value of sharing research data is widely recognised by the research community and funders are setting in place stronger policy requirements for researchers to share data. But the costs to researchers in sharing their data can be considerable and the incentives are sometimes few and far between. A recent report from the cross-disciplinary Expert Advisory Group on Data Access highlights the need for a shift in cultures to provide greater support for researchers in sharing data and greater recognition for those who do it well.