Are the lists of questionable journals reasonable: A case study of early warning journal lists.

The use of lists of questionable journals as a means to ensure research quality and integrity is the subject of an ongoing debate due to their ambiguous criteria. To assess the reasonableness of these lists from a typological perspective, we examined how effectively they reflect differences in bibliometric attributes among distinct groups and whether these differences are consistent. Using the Early Warning Journal Lists from the National Science Library of the Chinese Academy of Sciences as a case study, we categorized listed journals by warning levels and publication years. Our findings indicate potential inconsistencies in the criteria used for assigning warning levels, as we observed varying degrees of differences (or their absence) among groups across different key academic indicators. Notably, when it comes to citation metrics like journal impact factor and journal citation indicator, it appears that these criteria may not have been considered for grouping, although this lack of clarity from the creators is apparent. This underscores the importance of conducting more scientific and thorough evaluations of lists of questionable journals, along with a greater emphasis on sharing precise standards and data. Our study also provides recommendations for future iterations of such lists by different institutions.

Academic journals cannot simply require authors to declare that they used ChatGPT.

This letter to the editor points out weaknesses in the editorial policies of some academic journals regarding the use of ChatGPT-generated content. Editorial policies should provide more specific details on which parts of an academic paper are allowed to use ChatGPT-generated content. If authors use ChatGPT-generated content in the conclusion or results section, it may harm the academic paper's originality and, therefore, should not be accepted.

Letter to editor: Academic journals should clarify the proportion of NLP-generated content in papers.

This letter to the editor argues that if academic journals are willing to accept papers that include NLP-generated content under certain conditions, editorial policies should clarify the proportion of NLP-generated content in the paper. Excessive use of NLP-generated content should be considered as academic misconduct.

Why do master's students of humanities and social sciences publish papers in Chinese-language predatory journals? A qualitative study based on Grounded Theory.

In China, master's students in humanities and social sciences (HSS) are becoming the main target of Chinese-language predatory journals. Existing research has not paid enough attention to why these students publish papers in Chinese-language predatory journals. This research interviewed 30 HSS master's students with different majors using semi-structured interviews and Grounded Theory to analyze the data; it found that research discrimination, research context, self-awareness, and individual demand are the main reasons why students publish papers in Chinese-language predatory journals. This study provides the following suggestions in an effort to solve the problem of Chinese-language predatory journals. First, the Chinese government should draw up a blacklist of Chinese-language predatory journals. Second, the research evaluation departments of Chinese universities and research institutions should evaluate the research results of HSS master's students based on this list. Third, Chinese universities or scientific research institutions should strengthen the training of HSS master tutors and increase their awareness of Chinese-language predatory journals. And finally, Chinese HSS master's students should be taught about the hazards of Chinese-language predatory journals in research integrity and ethics courses, and refuse to publish papers in Chinese-language predatory journals.

Status bias in Chinese scholarly publishing: an exploratory study based on mixed methods.

The academic community requires not only responsible research but also responsible academic journals. An exploratory study of Chinese-language academic journals that used mixed methods found Chinese-language academic journals on the humanities and social sciences exhibiting a widespread status bias. Most of them summarily rejected submissions from junior researchers and students without paying due attention to the quality of the research itself. The main reasons for this problem are editorial department resources, the scientific research evaluation system, the editorial department culture, and the wider academic environment. This study recommends that Chinese-language academic journals join the Committee on Publication Ethics, other publishing ethics organizations, and the "Responsible Journals" program as soon as possible.

Characteristics of blacklisted journals: Evidence from Chinese-language academic journals.

Some institutions have issued blacklists of academic journals in China and use them as a basis for research evaluation. However, due to a lack of transparent formulation criteria, the characteristics of blacklisted journals remain unclear. Using blacklisted academic journals of the East China University of Political Science and Law, this study analyzed differences in characteristics between blacklisted and non-blacklisted journals via web surveys and statistical analyses. Statistically significant differences were detected for article review time, article processing charges (APCs), the number of editorial board members, and the journal impact factor. There was no significant difference in the number of editors. While there is scientific merit in creating and publishing a blacklist of academic journals, the list development process requires more rigorous evaluation and a public process of development.