IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v58y2024i4d10.1007_s11135-024-01837-6.html
   My bibliography  Save this article

The extreme upper tail of Japan’s citation distribution reveals its research success

Author

Listed:
  • Alonso Rodríguez-Navarro

    (Universidad Politécnica de Madrid
    Universidad Complutense de Madrid)

  • Ricardo Brito

    (Universidad Complutense de Madrid)

Abstract

A number of indications, such as the number of Nobel Prize winners, show Japan to be a scientifically advanced country. However, standard bibliometric indicators place Japan as a scientifically developing country. The present study is based on the conjecture that Japan is an extreme case of a general pattern in highly industrialized countries. In these countries, scientific publications come from two types of studies: some pursue the advancement of science and produce highly cited publications, while others pursue incremental progress and their publications have a very low probability of being highly cited. Although these two categories of papers cannot be easily identified and separated, the scientific level of Japan can be tested by studying the extreme upper tail of the citation distribution of all scientific articles. In contrast to standard bibliometric indicators, which are calculated from the total number of papers or from sets of papers in which the two categories of papers are mixed, in the extreme upper tail, only papers that are addressed to the advance of science will be present. Based on the extreme upper tail, Japan belongs to the group of scientifically advanced countries and is significantly different from countries with a low scientific level. The number of Clarivate Citation laureates also supports our hypothesis that some citation-based metrics do not reveal the high scientific level of Japan. Our findings suggest that Japan is an extreme case of inaccuracy of some citation metrics; the same drawback might affect other countries, although to a lesser degree.

Suggested Citation

  • Alonso Rodríguez-Navarro & Ricardo Brito, 2024. "The extreme upper tail of Japan’s citation distribution reveals its research success," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(4), pages 3831-3844, August.
  • Handle: RePEc:spr:qualqt:v:58:y:2024:i:4:d:10.1007_s11135-024-01837-6
    DOI: 10.1007/s11135-024-01837-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-024-01837-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11135-024-01837-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Miranda, Ruben & Garcia-Carpintero, Esther, 2018. "Overcitation and overrepresentation of review papers in the most cited papers," Journal of Informetrics, Elsevier, vol. 12(4), pages 1015-1030.
    2. Sonia R. Zanotto & Cristina Haeffner & Jorge A. Guimarães, 2016. "Unbalanced international collaboration affects adversely the usefulness of countries’ scientific output as well as their technological and social impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1789-1814, December.
    3. Ludo Waltman & Nees Jan van Eck & Anthony F. J. van Raan, 2012. "Universality of citation distributions revisited," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 72-77, January.
    4. Ludo Waltman & Nees Jan van Eck & Anthony F. J. van Raan, 2012. "Universality of citation distributions revisited," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(1), pages 72-77, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Javier Ruiz-Castillo, 2013. "The role of statistics in establishing the similarity of citation distributions in a static and a dynamic context," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 173-181, July.
    2. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "On the interplay between normalisation, bias, and performance of paper impact metrics," Journal of Informetrics, Elsevier, vol. 13(1), pages 270-290.
    3. You, Taekho & Park, Jinseo & Lee, June Young & Yun, Jinhyuk & Jung, Woo-Sung, 2022. "Disturbance of questionable publishing to academia," Journal of Informetrics, Elsevier, vol. 16(2).
    4. Giancarlo Ruocco & Cinzia Daraio, 2013. "An empirical approach to compare the performance of heterogeneous academic fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 601-625, December.
    5. Ruiz-Castillo, Javier & Costas, Rodrigo, 2018. "Individual and field citation distributions in 29 broad scientific fields," Journal of Informetrics, Elsevier, vol. 12(3), pages 868-892.
    6. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "How important is choice of the scaling factor in standardizing citations?," Journal of Informetrics, Elsevier, vol. 6(4), pages 645-654.
    7. Ruiz-Castillo, Javier & Waltman, Ludo, 2015. "Field-normalized citation impact indicators using algorithmically constructed classification systems of science," Journal of Informetrics, Elsevier, vol. 9(1), pages 102-117.
    8. W Benedikt Schmal, 2023. "The X Factor: Open Access, New Journals, and Incumbent Competitors," Working Papers of Department of Management, Strategy and Innovation, Leuven 723956, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
    9. S. R. Goldberg & H. Anthony & T. S. Evans, 2015. "Modelling citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1577-1604, December.
    10. Andrea Bonaccorsi & Cinzia Daraio & Stefano Fantoni & Viola Folli & Marco Leonetti & Giancarlo Ruocco, 2017. "Do social sciences and humanities behave like life and hard sciences?," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 607-653, July.
    11. Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," Journal of Informetrics, Elsevier, vol. 8(4), pages 917-934.
    12. Zhihui Zhang & Ying Cheng & Nian Cai Liu, 2015. "Improving the normalization effect of mean-based method from the perspective of optimization: optimization-based linear methods and their performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 587-607, January.
    13. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2024. "Rank analysis of most cited publications, a new approach for research assessments," Journal of Informetrics, Elsevier, vol. 18(2).
    14. Vîiu, Gabriel-Alexandru, 2018. "The lognormal distribution explains the remarkable pattern documented by characteristic scores and scales in scientometrics," Journal of Informetrics, Elsevier, vol. 12(2), pages 401-415.
    15. Thelwall, Mike & Wilson, Paul, 2014. "Distributions for cited articles from individual subjects and years," Journal of Informetrics, Elsevier, vol. 8(4), pages 824-839.
    16. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    17. Xin Li & Xuli Tang & Wei Lu, 2024. "How biomedical papers accumulated their clinical citations: a large-scale retrospective analysis based on PubMed," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3315-3339, June.
    18. Loet Leydesdorff & Ping Zhou & Lutz Bornmann, 2013. "How can journal impact factors be normalized across fields of science? An assessment in terms of percentile ranks and fractional counts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 96-107, January.
    19. Thelwall, Mike, 2016. "Are the discretised lognormal and hooked power law distributions plausible for citation data?," Journal of Informetrics, Elsevier, vol. 10(2), pages 454-470.
    20. Zhihui Zhang & Ying Cheng & Nian Cai Liu, 2014. "Comparison of the effect of mean-based method and z-score for field normalization of citations at the level of Web of Science subject categories," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1679-1693, December.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:58:y:2024:i:4:d:10.1007_s11135-024-01837-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.