Hallucinated citations produced by generative artificial intelligence may constitute research misconduct when citations function as data in scholarly papers
https://www.tandfonline.com/doi/full/10.1080/08989621.2026.2645390#abstract
ABSTRACT: In this article, we discuss the growing problem of hallucinated citations produced by Generative Artificial Intelligence (GenAI) in scholarly research and writing. We argue that GenAI hallucinated citations might qualify as a provable instance of research misconduct under the U.S. federal regulations when a) the researcher uses a GenAI tool to produce hallucinated (i.e., nonexistent) citations for a research document; b) the citations function as data because they directly support research findings, as in, for example, review articles or bibliometric studies; and c) the researcher demonstrates indifference to the risk of fabrication of the data (i.e. citations) because they did not check the GenAI’s output for veracity and accuracy.
Other types of problematic citations such as bibliometrically incorrect citations, or contextually inaccurate citations, are indicative of poor scholarship and irresponsible behavior, but do not qualify as research misconduct. Recognizing that GenAI hallucinated citations could be regarded as research misconduct in certain cases will hopefully encourage researchers to take this problem more seriously than they do now. In partnership with scientific institutions, funders and professional societies, the scholarly community should work on establishing, promoting, and enforcing standards for responsible use of AI in research, including standards pertaining to citation practices. (
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Research culture and integrity in Japan: A qualitative study
https://link.springer.com/article/10.1007/s11948-026-00591-2
ABSTRACT: There have been numerous instances of research and funding fraud by Japanese researchers that have discredited Japanese research, and thus ministries, universities and other institutions have attempted to prevent research misconduct and promote research integrity through measures such as policy amendments and education. However, it is unclear whether those measures have been effective, because research misconduct continues to occur.
In this study, we conducted focus group interviews with 25 participants, including both researchers and administrators, from various academic disciplines. The interviews were guided by seven semi-structured questions based on the Promoting Integrity as an Integral Dimension of Excellence in Research protocol. Our analysis of the resulting data identified 20 themes.
Regarding research integrity, participants highlighted boundary ambiguity and the need for a new definition. In relation to the research culture, the following barriers were identified: the laboratory environment, job security for junior researchers and middle-senior researchers, and pressures faced by principal investigators. In terms of policies, participants observed that research integrity regulations were not widely disseminated, and proposed several methods to provide education, including informational materials.
Regarding improvements to the current environment, participants mentioned performance evaluation, an open research environment, a supportive research environment, and sharing of previous cases. While numerous issues were raised, several solutions were also proposed. We found that gaining access to the collective knowledge of faculty, students, and administrators is the best way to foster a strong research culture and develop research integrity. (
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How to get there from here? Barriers and enablers on the road towards reproducibility in research
https://journal.trialanderror.org/pub/barriers-enablers/release/1?readingCollection=dfde1f5c
ABSTRACT: Reproducibility of research is a hotly debated topic, including aspects like causes and consequences of low levels of reproducibility. While some research fields have led the way and introduced various reproducibility practices and procedures, the call for efforts to ‘improve’ reproducibility in research has not come without criticisms.
The current study uses a future studies methodology to gather perceptions of developments in the research ecosystem related to reproducibility issues. It draws on input from representatives of four main stakeholder categories: scholarly publishers, funding agencies, qualitative social scientists and machine learning researchers.
Particularly, it discusses the enablers and barriers that members of these stakeholder communities foresee on the road towards a research ecosystem that is more conducive to reproducibility. The study finds that enablers and barriers can be categorised into five main clusters.
The factors most prominently mentioned as potentially supporting or hindering a desired future are located within research culture, including norms, values and shared definitions; and in the infrastructure required to engage in reproducibility practices, including repositories, support staff, and digital infrastructure. Three other clusters of factors put forth by participants relate to policy efforts required to incentivise reproducibility practices; training and education to empower researchers and support staff to engage in reproducibility practices; and the financial resources required to facilitate the transition towards a desired future and to specifically fund replication studies.
This manuscript also identifies several tensions between enablers and barriers perceived by diverse stakeholders and concludes with recommendations for addressing these. (
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