Producción Científica

Today, academics and researchers constantly strive to achieve more in their respective fields. Their achievements are measured mainly by how many publications they have within publication venues and their work’s recognition (impact), which is usually determined through its citations, subsequently affecting how funding and awards are obtained. To assess the importance academics place on citations when evaluating scientists for recruitment or promotion, the authors of surveyed faculty members from the top 10 ranked universities globally. Their findings indicate that the majority of faculty members take citation counts into account when assessing candidates, which is reflected at a local and national level. The availability of huge curated bibliographic databases such as Elsevier Scopus and Web of Science (WoS) over the past twenty years has led decision-makers involved in promotions, funding, and strategic direction to increasingly request data related to individual studies or scholars (such as scientific articles, PhD students, postdoctoral researchers, and faculty members) as well as groups of individuals and articles (such as journals, universities, institutions, and companies) to support their decisions. Publication practices in the fields of social sciences and humanities differ from those used for most natural science publications. Consequently, their research output is often inadequately represented in the aforementioned journal-based databases typically used for bibliometric analysis. This issue is particularly pronounced for non-English journals, which are notably underrepresented, as well as for conference papers, books, and edited volumes. An alternative to the more traditional journal-based systems of WoS and Scopus is Google Scholar (hereafter referred to as GS), which is one of the most comprehensive databases currently available. Several works, e.g., have analyzed the relative coverage between Google Scholar and Scopus. As soon as scientists realized that a significant proportion of their evaluation was based on these purely quantitative methods, some started to take advantage of the system. At first, the prevalence of plagiarism was sparse. However, many members of the academic community soon began consistently striving to optimize their performance through two key approaches: (a) increasing the number of papers they have authored and (b) increasing their impact, i.e., the number of citations received by these papers. While it is of course acceptable for a scientist to increase their productivity and the quality of their research impact to attract more citations, several malpractices started making their appearance in the academic landscape. Some malpractices used to optimize authorship include buying authorship and generating large authorship lists by merging and splitting articles. Some of the malpractices used to optimize impact include the use of excessive self-citations, citation circles, and coercive citations, as well as uploading fake documents, editorial grouping, and using Generative AI tools. Most of these malpractices are easily achievable in Google Scholar since it is editable by the end user, but some, such as self-citations, citation circles, and coercive citations, are also a problem for curated bibliographic databases. Additionally, quality control issues in Google Scholar exacerbate the situation. In the remainder of this editorial, we will briefly describe the mechanisms behind these malpractices and provide some ideas for reducing the problem.