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pmid: 37991609
As stewards of public money, government funding agencies have the obligation and responsibility to uphold the integrity of funded research. Despite an increasing amount of empirical studies examining research-related misconduct, a majority of these studies focus on retracted publications. How agencies spot funding-relevant wrongdoing and what sanctions the offenders face remain largely unexplored. This is particularly true for public funding agencies in emerging science powers. To amend this oversight, we retrieved and analyzed all publicized investigation results from China's largest basic research funding agency over the period from 2005 to 2021. Our findings reveal that both the "police patrol" and "fire alarm" approaches are used to identify misconduct and deter funding-related fraud in China. The principal triggers for investigations are journal article retractions, whistleblowing, and plagiarism detection software. Among the six funding-related misconduct types publicized and punished, the top three are: (1) fraudulent papers, (2) information fabrication and/or falsification in the research proposal, and (3) proposal plagiarism. The most common administrative sanctions are debarment and reclamation of grants. This article argues that more systematic research and cooperation among stakeholders is needed to cultivate research integrity in emerging science powers like China. Specific training and education should be provided for young scientists to help them avoid the pitfall of academic misconduct.
China, Scientific Misconduct, Humans, Criminals, Empirical Research, Plagiarism
China, Scientific Misconduct, Humans, Criminals, Empirical Research, Plagiarism
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |