The article addressed to the problem of the statistical relationship (correlation) between citation of individual articles or magazines in general on the one hand and a real assessment of the scientific community on the other hand. The problem is studied in relation to applied mathematics; it is based on research, organized by the Australian Research Council (with the assistance of various public organizations and experts) in the 2010 year. Data from these researches appear to be interesting, because they formed the basis for the article «Nefarious numbers», which won wide popularity and became fundamental for the science studies (in the problem, relating to value of the probabilistic relationship between citation and scientific significance). Statistics data of «Nefarious numbers» reproduced in detailsand accurately researched by methods of the correlation analysis (as opposed to an externally and popular presentation of the «Nefarious numbers», where methods of the correlation analysis in no way demonstrated). As a result, the conclusions of the «Nefarious numbers» are specified and complemented to some extent. The article can be useful for research in the scientometrics and the sociology of science. The algorithm of comprehensive and wide applying methods of the correlation analysis to the category “Mathematics, Applied”, which described in the article, can be generalized and used without changes to any other category of science, about which there is ambiguity and questions in the value of the statistical relationship between citation and scientific significance.
Translated title of the contributionABOUT THE STATISTICAL RELATIONSHIP BETWEEN EXPERT JUDGMENT FOR SCIENTIFIC JOURNALS AND THEIR IMPACT FACTORS
Original languageRussian
Pages (from-to)583-592
Number of pages10
JournalНаучные ведомости Белгородского государственного университета. Серия: Философия. Социология. Право
Volume44
Issue number4
DOIs
Publication statusPublished - 2019

    GRNTI

  • 12.00.00 SCIENCE OF SCIENCE

    Level of Research Output

  • VAK List

ID: 12717959