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Research integrity, a cornerstone of scholarly publishing, faces challenges from the surge of ‘fake’ articles—fully or partially fabricated works that undermine genuine academic efforts. The emergence of paper mills has escalated this issue, introducing a level of scale and sophistication to academic misconduct that is both recent and concerning.
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The Latest from STM
VIEW ALL NEWSNew research paper highlights key questions to tackle the growing threat of paper mills
Research paper mills — covert organizations that produce fraudulent manuscripts for profit — pose a significant threat to science and scholarship. These unethical entities scale their operations using AI, sell authorship positions, and manipulate peer review, eroding trust in research and slowing progress in critical areas such as innovation, healthcare, and policy. United2Act — a…
Creative rights in AI Coalition calls on Government to protect copyright as GAI policy develops
We’re proud to announce that STM has joined the newly formed Creative Rights in AI Coalition. As generative AI continues to reshape the landscape of innovation, protecting copyright and fostering collaboration between the creative and tech sectors has never been more crucial. We’re calling on the government, tech sector, and creators to join us in…
Strengthening global collaboration: Caroline Sutton’s annual visit to Japan highlights key advances in Open Access and scholarly communication
Caroline Sutton’s annual visit to Japan in late October was, as always, a productive journey marked by a full agenda of strategic meetings, collaborations and community engagement. At-a-glance: a packed itinerary Caroline’s itinerary included high-level external meetings with key government bodies like the Cabinet Office and the Ministry of Education, Culture, Sports, Science, and Technology…
New report: Feasibility of technical solutions for the detection of falsified images in research
Amidst the ongoing issues of research integrity and paper mills, image integrity is a growing concern. The rise of generative AI poses significant additional risks, as it allows for the generation of images and other types of data that are very hard — if not impossible — to detect with current technologies. For this reason,…
