Introduction

Research integrity is concerned with the conduct and practices of researchers, involving issues pertaining to authorship, fabrication and falsification, paper mills and so on. The emergence of generative AI tools supported by machine learning, such as ChatGPT, has also raised questions about authenticity, copyright and the future of scholarly communication. Research integrity is of utmost importance, because research and researchers can only be trusted if research studies are conducted in good faith and if research articles are not used as a vehicle for peddling unsubstantiated facts and unjustified claims. The ethos of science, commonly known as ‘Mertonian norms’, proposed by the sociologist of science, Robert Merton (1973, originally published 1942), are as follows:

• • Universalism: The acceptance or rejection of research findings is not dependent on personal or social attributes such as race, nationality, religion, class and personal qualities.

• • Communism: The imperative for communication of findings is linked to the conception of science as part of the public domain, meaning that full and open communication shall form the basis of scholarly communication.

• • Disinterestedness: The trust of scientific research is based on the disinterestedness of researchers rather than personal, commercial or political gains.

• • Organised sceptism: Research data and scientific claims are open for scrutiny and subject to critique and revision.

The Mertonian norms speak to the basis on which the integrity and conduct of research should be upheld. On the one hand, research findings can be distorted if a research study is under commercial or political influence. On the other hand, it is problematic if the acceptance or rejection of a manuscript is affected by the personal or social attributes of an author, which can result in important research findings being neglected. Researchers are generally trusted to advance knowledge and conduct research for public good. In fact, research findings based on fabricated data or fraudulent practices can lead to dire consequences, especially when they are reported in the mass media. One infamous example is the false reporting of the MMR vaccine as a cause of autism. Although the research article was eventually retracted, the reporting has been part of the anti-vaccination discourse. Worse, the reports of misconduct can lead to distrust in researchers and research institutions.

In recent years, there have been increased reports of fraudulent research and retraction.