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  • Research Paper
    Edita Gzoyan, Aram Mirzoyan, Anush Sargsyan, Mariam Yeghikyan, Domenico A. Maisano, Shushanik Sargsyan
    Journal of Data and Information Science. https://doi.org/10.2478/jdis-2023-0011
    Accepted: 2023-04-26
    Abstract (94) PDF (674KB) ( 54 )
    Purpose: Nearly 122 scientific journals are currently being published in Armenia—of which only six are indexed by WoS and/or Scopus databases. The majority of the national journals are published in the Armenian language, solely possessing abstracts written in English, although there are also English-language and multi-language journals with articles not only in Armenian but also in other foreign languages. The aim of this article is to study the visibility of the (non-indexed) national Armenian journals in the WoS database through citation analysis. In consideration of the existence of a relevant Armenian “diaspora” in the world, this article also attempts to estimate its impact in terms of citation statistics.
    Design/methodology/approach: For this end, we have identified citations to the national/domestic Armenian journals in the WoS database in comparison with the share of citations received from “diaspora” researchers (researchers of Armenian origin born in foreign countries and those originally from Armenia who have emigrated to foreign countries).
    Findings: Among the 116 Armenian domestic journals analyzed (not indexed by WoS), only 47 were found to be cited in WoS. Of these journals, almost 12% are citations by “diaspora” researchers, most of which concern Social Science and Humanities journals.
    Research limitations: Although the surnames of Armenians end with -i(y)an, sometimes, the Diaspora Armenians, surnames are changed or modified or they are not ending with -i(y)an, in this case we may fail to identify them.
    Practical implications: This study can help to build new, more deep and comprehensive relations with scientific diasporas.
    Originality/value: This study offers a new understanding of multifaced research collaboration with scientific diasporas and their role in internationalization of domestic journals.
  • Katerina Guba, Alexey Zheleznov, Elena Chechik
    Journal of Data and Information Science. https://doi.org/10.2478/jdis-2023-0010
    Accepted: 2023-04-23
    Abstract (100) PDF (1081KB) ( 32 )
    Purpose: This study examines the effects of using publication-based metrics for the initial screening in the application process for a project leader. The key questions are whether formal policy affects the allocation of funds to researchers with a better publication record and how the previous academic performance of principal investigators is related to future project results.
    Design/methodology/approach: We compared two competitions, before and after the policy raised the publication threshold for the principal investigators. We analyzed 9,167 papers published by 332 winners in physics and the social sciences and humanities (SSH), and 11,253 publications resulting from each funded project.
    Findings: We found that among physicists, even in the first period, grants tended to be allocated to prolific authors publishing in high-quality journals. In contrast, the SSH project grantees had been less prolific in publishing internationally in both periods; however, in the second period, the selection of grant recipients yielded better results regarding awarding grants to more productive authors in terms of the quantity and quality of publications. There was no evidence that this better selection of grant recipients resulted in better publication records during grant realization.
    Originality: This study contributes to the discussion of formal policies that rely on metrics for the evaluation of grant proposals. The Russian case shows that such policy may have a profound effect on changing the supply side of applicants, especially in disciplines that are less suitable for metric-based evaluations. In spite of the criticism given to metrics, they might be a useful additional instrument in academic systems where professional expertise is corrupted and prevents allocation of funds to prolific researchers.
  • Jaime A. Teixeira da Silva, Serhii Nazarovets
    Journal of Data and Information Science. https://doi.org/10.2478/jdis-2023-0009
    Accepted: 2023-04-19
    Abstract (64) PDF (304KB) ( 24 )
    Cancer research is occasionally described as being in a reproducibility crisis. The cancer literature has ample papers retracted due to misconduct, including the use of paper mills, invalid authorship, or fake data. The objective of this paper was to gain an appreciation of the balance of retractions and associated retraction notices of 23 retracted Cancer Biotherapy and Radiopharmaceuticals papers associated with paper mills. By 23 March 2023, these retracted papers had already accumulated 287 citations according to Web of Science Core Collection, 253 according to Scopus, and 365 according to Google Scholar, i.e., metrically speaking, they were highly rewarded. All authors had an affiliation (71% being a hospital) in China. Most (12/21; 57%) of corresponding authors had emails with a @163.com suffix. Four of the retraction notices (i.e., 17%) explicitly indicated paper mills as a reason for retraction although, in general, the retraction notices lacked details and background that could assist readers’ understanding of the retractions.
  • Research Paper
    Meiling Li, Yang Zhang, Yang Wang
    Journal of Data and Information Science. https://doi.org/10.2478/jdis-2023-0008
    Accepted: 2023-04-18
    Abstract (80) PDF (1909KB) ( 50 )
    Purpose: With the availability of large-scale scholarly datasets, scientists from various domains hope to understand the underlying mechanisms behind science, forming a vibrant area of inquiry in the emerging "science of science" field. As the results from the science of science often has strong policy implications, understanding the causal relationships between variables becomes prominent. However, the most credible quasi-experimental method among all causal inference methods, and a highly valuable tool in the empirical toolkit, Regression Discontinuity Design (RDD) has not been fully exploited in the field of science of science. In this paper, we provide a systematic survey of the RDD method, and its practical applications in the science of science.
    Design/methodology/approach: First, we introduce the basic assumptions, mathematical notations, and two types of RDD, i.e., sharp and fuzzy RDD. Second, we use the Web of Science and the Microsoft Academic Graph datasets to study the evolution and citation patterns of RDD papers. Moreover, we provide a systematic survey of the applications of RDD methodologies in various scientific domains, as well as in the science of science. Finally, we demonstrate a case study to estimate the effect of Head Start Funding Proposals on child mortality.
    Findings: RDD was almost neglected for 30 years after it was first introduced in 1960. Afterward, scientists used mathematical and economic tools to develop the RDD methodology. After 2010, RDD methods showed strong applications in various domains, including medicine, psychology, political science and environmental science. However, we also notice that the RDD method has not been well developed in science of science research.
    Research Limitations: This work uses a keyword search to obtain RDD papers, which may neglect some related work. Additionally, our work does not aim to develop rigorous mathematical and technical details of RDD but rather focuses on its intuitions and applications.
    Practical implications: This work proposes how to use the RDD method in science of science research.
    riginality/value: This work systematically introduces the RDD, and calls for the awareness of using such a method in the field of science of science.