New Dimensions Partnership with ISSI Makes It Easy (and Free!) for Researchers to Study the Science of Science
International Society for Scientometrics and Informetrics (ISSI) and Digital Science have joined forces to make Dimensions and Altmetric data available to ISSI members at scale, and at no cost for scientometric research purposes.
Turning the Tables: A University League-Table Based On Quality Not Quantity
League tables predominantly reward measures of research output, such as publications and citations, and may therefore be promoting poor research practices by encouraging the “publish or perish” mentality. The authors examined whether a league table could be created based on good research practice.
Should We Trust Meta-Analyses with Meta-Conflicts of Interest?
There are a couple of angles to look at researcher conflict of interest from. One is that a conflict could distort their work, tilting findings and claims away from "the truth". The other is for the way the work is received, not how it is done: authors' perceived conflicts could damage credibility. How does this translate to authors of systematic reviews and meta-analyses? Are the issues the same, no matter the type of study? I've been thinking about that a lot lately. I was one of the external stakeholders consulted as part of the Cochrane Collaboration's review of its conflict of interest policy for their systematic reviews editorial teams. As they explain, they are looking to strengthen their approach to financial conflicts, and "consider a wider range of possible inherent biases". In biomedicine at least, systematic reviewers/meta-analysts are widely seen as arbiters on the state of knowledge. Their work often guides individual decisions, policy, and funding. I think that
Calibrating the Scientific Ecosystem Through Meta-Research
Whilst some scientists study insects, molecules, brains, or clouds, other scientists study science itself. Meta-research, or “research-on-research”, is a burgeoning discipline that investigates efficiency, quality, and bias in the scientific ecosystem.