Ask the Community: What’s Next for the OMB Rule Change?
Today, we asked the community: What key message(s) do you want policymakers to take from the responses submitted to the OMB?
Today, we asked the community: What key message(s) do you want policymakers to take from the responses submitted to the OMB?
Research integrity demands stronger safeguards in order to protect the scholarly record. But for editors, when new integrity measures are introduced, they do not replace existing tasks; they are added alongside them, compounding workloads and responsibilities.
Today’s post is the second in a series arguing that fractures appearing across research systems are symptoms of a mismatch within today’s research ecosystem.
Today’s guest blogger questions the operating model around scholarly research and asks why these capabilities are so difficult to sustain at scale.
Open Science 2.0 must focus not only on access, but also on trust, interpretation, learning, and effective communication. The challenge facing the scholarly publishing ecosystem is ensuring that what is open is also trustworthy, understandable, and genuinely useful.
Today’s guest post presents outcomes of the WCRI’s (World Conferences on Research Integrity) Focus Track to address this gap in clarity and standardization of AI disclosure.
Today’s post asks us to acknowledge the role of AI in peer review and ensure practical guidance and policies that help scholars respond with consistency and confidence.
Building robust citation and attribution into generative AI systems are foundational to usage, credit and trust. We need to expect more from AI.
China’s publishing ambitions create genuine competitive pressures, but they also open opportunities for collaboration and highlight challenges that neither side can address alone
China is no longer simply a major contributor to global research output; it is increasingly becoming a key force shaping the future of scholarly publishing. Understanding what is actually happening, and why, is the necessary first step before considering how publishers should respond.
In honor of Global Accessibility Awareness Day, today’s post shares results from an experiment with qualitative data analysis — demonstrating that, while AI can detect patterns, humans must decide what those patterns mean.
Today’s guest post asserts that trust won’t be restored by “better messaging” alone, but via better incentives, more disciplined public communication, and really listening to the people who have walked away from us.
Today’s guest post sounds an alarm about the use of AI in research and warns that no amount of computational efficiency can compensate for the loss of our capacity for human thought.
Today’s guest bloggers call publishers to lean into, rather than away from, their liability for science integrity and rigor.
AI in science should not be viewed merely as a productivity tool layered onto existing workflows. It represents a structural shift in how knowledge moves through society, and therefore in how scientific authority is established and maintained.