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?
If libraries are civic institutions that structure society’s relationship to knowledge, and generative AI is poised to reshape discovery whether libraries act or not, will library leaders will develop strategies that preserve trust, equity, and sustainability?
Building on SSP’s spring results of the individual compensation and benefits study, Melanie Dolechek shares insights from the organizational survey — a slide of the survey data that provides useful benchmarks on policies and practices across publishing organizations.
If science is to be both honest and healthy, we must accept that statistically non-significant results are part of reality. The SAMPL guidelines, if adopted widely by scholarly publishers and journal editors, hold a solution for authors who worry their results are not “significant.”
Today, we speak with Prof. Yana Suchikova about GAIDeT, the Generative AI Delegation Taxonomy, which enables researchers to disclose the use of generative AI in an honest and transparent way.
The STM Association offers a classification scheme for the various possible uses of AI, including GenAI, in the preparation of manuscripts.
Today, we talk to thought leaders Helen King and Chris Leonard, who offer a nuanced look at how peer review might adapt, fracture, or reinvent itself in the AI era.
The future of peer review isn’t about choosing between humans and AI, or between speed and quality, but about combining the strengths of both to enable speed with quality, to ensure quality, ethics, and trust in the scholarly record.
Peer Review Quality Ratings could offer a powerful step toward restoring faith in the scholarly research system, highlight exemplary practices, and ensure that robust, verified science continues to illuminate the path forward for humanity.
What can you expect from this fall’s New Directions in Scholarly Publishing Seminar in Washington, DC?
Today’s post discusses research metrics and their relationship to research integrity, inclusivity, and long-term impact.
NISO’s Open Discovery Initiative (ODI) survey reflects the positive and negative expectations of generative AI in web-scale discovery tools.
This post explores author, reviewer, and publisher ethics and responsibilities related to the use of AI in coding and publishing research software.
Summing up the Committee on Publication Ethics (COPE) Forum discussion on Emerging AI Dilemmas in Scholarly Publishing, which explored the many challenges AI presents for the scholarly community.
FAIR represents the best opportunity of the models under consideration to ensure that research information services receive appropriate recognition and sustainable funding