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Citation bias in medical journals

Author

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  • T. Ojasoo
  • J. C. Doré

    (Muséum National d'Histoire Naturelle)

Abstract

Multivariate statistical analysis of the citation profiles of urology and related journals (i.e. the relative extent to which each journal cites itself and other journals within a set) has highlighted hidden correlations. We reveal the existence of a ‘transatlantic’ rift in citation practice and of a confined discipline-oriented world which interfaces weakly with many other disciplines. We also interpret the results of our analyses in terms of basic and clinical research and examine whether there is a time-related selectivity in citation. Taken together, our results call for a serious appraisal of present-day research trends and of their evaluation. The open question is how to create a terrain that will foster original, possibly interdisciplinary, research in developed nations whilst maintaining cultural individuality.

Suggested Citation

  • T. Ojasoo & J. C. Doré, 1999. "Citation bias in medical journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 45(1), pages 81-94, May.
    • Handle: RePEc:spr:scient:v:45:y:1999:i:1:d:10.1007_bf02458469
    DOI: 10.1007/BF02458469
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    References listed on IDEAS

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    1. J. C. Gower & G. J. S. Ross, 1969. "Minimum Spanning Trees and Single Linkage Cluster Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 18(1), pages 54-64, March.
    2. Jean‐Christophe Doré & Tiiu Ojasoo & Yoshiko Okubo & Thomas Durand & Gérard Dudognon & Jean‐François Miquel, 1996. "Correspondence factor analysis of the publication patterns of 48 countries over the period 1981–1992," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 47(8), pages 588-602, August.
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    Cited by:

    1. Tiiu Ojasoo & Hervé Maisonneuve & Jean-Christophe Doré, 2001. "Evaluating publication trends in clinical research: How reliable are medical databases?," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(3), pages 391-404, March.
    2. Michael Färber & Melissa Coutinho & Shuzhou Yuan, 2023. "Biases in scholarly recommender systems: impact, prevalence, and mitigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2703-2736, May.

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