Guest Post — Could AI Help Fix Peer Review, or Will it Only Make Things Worse?
Today’s post asserts that peer review, which is still of vital importance to science, is clearly failing in the current age — could AI save the day?
Today’s post asserts that peer review, which is still of vital importance to science, is clearly failing in the current age — could AI save the day?
Today’s guest post offers a review of a panel of publishers and editors discussing the pros and cons of using Generative AI, along with ethical and policy implications.
Today’s guest post asks readers to reckon with the idea that knowledge reflects power, and the global knowledge economy excludes the Global South.
Today’s guest blogger proposes the “Continuum of Consensus” as a solution to shore up research integrity, peer review, and the public trust in scholarly research.
Current AI disclosure guidelines are failing and driving AI use underground rather than making it transparent. In this follow-up post, I turn to the more challenging question: what publishers should do about it.
Only a negligible percentage of authors seem to actually be disclosing their AI use. Here’s why I think that’s the case.
Academic publishing ia reaching a breaking point. Unless we redesign it, we risk stalling the very progress we seek – with consequences impacting research, education and public trust in academia.
Today’s guest post summarizes the discussion in the recent EASE / STM / webinar, exploring the digital carbon footprint of scholarly publishing.
Today, Alison Mudditt reflects on a Charleston Conference session that asked: what would it take to make the scholarly communication system truly equitable, impactful, and future-ready?
A review of 12 major publishers finds that they display an average of 6 journal-level impact metrics on their platforms. The Journal Impact Factor is the only metric displayed on all 12.
Today’s guest blogger sees scholarly publishing at a critical inflection point and research suffering from a flawed incentive structure. Can systems thinking offer innovative solutions?
Today’s post discusses research metrics and their relationship to research integrity, inclusivity, and long-term impact.
As AI becomes a major consumer of research, scholarly publishing must evolve: from PDFs for people to structured, high-quality data for machines.
Catching up with the ongoing consolidation of the journals market — what has happened in the two years since this was last examined? And how does the market look if you add in a large number of relatively newly launched journals?
A scholarly communication ecosystem that relies on voluntary support rather than charging for access to content becomes radically less capable of keeping money in the system.