Confused and Ambivalent: Scholarly Authors and Creative Commons Licenses
An AAAS survey reveals authors’ concerns and confusion regarding open licensing of their work.
An AAAS survey reveals authors’ concerns and confusion regarding open licensing of their work.
We asked the Chefs for their thoughts on two important court decisions on the legality of using copyrighted materials for AI training.
A summary of the European Association of Science Editors (EASE) debate session, where Haseeb Irfanullah argued in favor of a motion declaring that journal editors do not need to worry about preventing the spread of misinformation, while Are Brean argued against it.
Have you been visited by Titivillus, the demon of typographical errors?
How does the Directory of Open Access Books navigate challenges to instill trust and transparency. Part 1 of 2.
The analysis of operational data is complex, dull, and unrewarding. It is also necessary. Three case studies of major journals and portfolios explain why.
A comprehensive set of recommendations designed to support researchers, peer-reviewed journals, and funding bodies in systematically incorporating intersectional perspectives have been formalized in the Guidelines for Intersectional Analysis in Science and Technology (GIST). Here we interview Londa Schiebinger, co-author of the Guidelines.
The most vital and enduring contribution of scholarly publishers is their role as gatekeepers — not as obstacles to knowledge but as stewards of quality, integrity, and trust.
While our understanding of climate change is shaped by academia, the climate crisis also shapes academia’s research and teaching in numerous ways. In this article, I explore the current climate change-academia relationship and touch upon some envisaged changes.
At the 3rd Generative AI Summit in London, global leaders and companies shared how they’re embedding generative AI into strategies, workflows, and products for commercial success, operational efficiency, and competitive advantage. Here, we’d like to share key takeaways and insights from multiple perspectives and explore what they mean for publishers.
It is time for OA proponents to engage in public debate with academic associations, universities and national funding agencies, because the widespread use of academic content in AI models poses significant risks for the research ecosystem.
I think human-dependent peer review has lost its human element, thus its relevance, so what we can do to install a new system by abandoning the present one?
Nicola Davies from IOPP details the publisher’s new data sharing requirements for authors.
What can be done to resolve concerns about image integrity in scientific publications?
I tried three different large language models (LLMs) to rewrite a potential article.