Guest Post: The STM Integrity Hub — Connecting the Dots in a Dynamic Landscape
An update on progress from the STM Research Integrity Hub.
An update on progress from the STM Research Integrity Hub.
As high profile cases about image integrity problems in scientific papers become more frequent, the community must consider how to overcome the issues with the manual image review process and the benefits of AI in rapidly detecting, and potentially preventing, these issues.
Christos Petrou presents evidence suggesting that growth in retractions has not been universal across regions and subject areas, and it is primarily driven by the industrial-scale activity of papermills (rather than the activity of individual researchers) and the growth of research from China.
Promoting research integrity is not just identifying bad behavior: problem articles can also be detected by the absence of ‘honest’ signals of integrity.
Leslie McIntosh names the emerging field of forensic scientometrics.
Research journals and the peer review process should not be the first line of defense in identifying research integrity issues. In today’s post, Angela Cochran calls for research institutions to take a larger role in validation and integrity checks.
The nationwide audit of retracted articles in China underscores the interconnectedness of stakeholders within the research ecosystem and emphasizes the importance of aligning incentives and priorities to foster a culture of integrity and accountability. Can similar efforts be applied globally to cultivate a culture of accountability and transparency?
Journal articles with ChatGPT authored text are being found. How common is this in the literature? And how, or better yet, when, is this problematic text slipping through to publication?
Fraud is undermining the integrity of the scholarly record. United2Act is striking back at paper mills.
Attribution has many virtues, but among them it can make visible the vast infrastructure of research for a public largely unaware or unconcerned with how much hard-won knowledge, including creative endeavor, that research has facilitated.
Should the authors’ institution make decisions regarding authorship disputes on a paper?
How do we define, track, and measure trust in scholarly publishing?
Balancing the anxiety and the excitement over the use of Large Language Models (LLMs) in scholarly publishing.
A report of the Chef’s panel on AI, Open content, and research integrity during the Frankfurt Book Fair.
Accountability is at the center of leadership. We must hold people, policies and structures to account and if we are struggling with tackling the hard questions, are we really doing the work?