Author
Listed:
- Gergely Ferenc Lendvai
- Aczél Petra
Abstract
The present study investigates how the five largest academic publishers (Elsevier, Springer, Wiley, Taylor & Francis, and SAGE) are responding to the epistemic and procedural challenges posed by generative AI through formal policy frameworks. Situated within ongoing debates about the boundaries of authorship and the governance of AI-generated content, our research aims to critically assess the discursive and regulatory contours of publishers’ authorship guidelines (PGs). We employed a multi-method design that combines qualitative coding, semantic network analysis, and comparative matrix visualization to examine the official policy texts collected from each publisher’s website. Findings reveal a foundational consensus across all five publishers in prohibiting AI systems from being credited as authors and in mandating disclosure of AI usage. However, beyond this shared baseline, marked divergences emerge in the scope, specificity, and normative framing of AI policies. Co-occurrence and semantic analyses underline the centrality of ‘authorship’, ‘ethics’, and ‘accountability’ in AI discourse. Structural similarity measures further reveal alignment among Wiley, Elsevier, and Taylor & Francis, with Springer as a clear outlier. Our results point to an unsettled regulatory landscape where policies serve not only as instruments of governance but also as performative assertions of institutional identity and legitimacy. Consequently, the fragmented field of PG highlights the need for harmonized, inclusive, and enforceable frameworks that recognize both the potential and risks of AI in scholarly communication.
Suggested Citation
Gergely Ferenc Lendvai & Aczél Petra, 2026.
"Artificial intelligence in academic practices and policy discourses across ‘Big 5’ publishers,"
Research Evaluation, Oxford University Press, vol. 35, pages 1-004..
Handle:
RePEc:oup:rseval:v:35:y:2026:i::p:rvag004.
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oup:rseval:v:35:y:2026:i::p:rvag004.. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/rev .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.