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Eugene Garfield: from the metrics of science to the science of metrics

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  • Gangan Prathap

    (Vidya Academy of Science and Technology
    A P J Abdul Kalam Technological University)

Abstract

Quantity and quality are Aristotelian categories. Ever since Galileo, the defining feature of Science is the accurate measure of quantity, e.g., time, length and mass, to begin with. Length and mass are size dependent. Quality remained an elusive category as it is a size-independent feature. It was Archimedes who first brought a revolution in physics by defining density as a size-independent attribute. A similar revolution was effected in the measurement of science when Eugene Garfield introduced the concept of the citation as a unit of measurement and from this, separated quantity (number of publications) from quality (impact). In this article, we interpret impact as a thermodynamic mean instead of a simplistic arithmetic mean. This opens up rich analogies with the conservation laws of mechanics and thermodynamic features linking disorder and unevenness to entropy. Also as in physics, considerations of dimensional homogeneity play a defining role. Without Garfield’s bold initiative, all this will have eluded us for some time.

Suggested Citation

  • Gangan Prathap, 2018. "Eugene Garfield: from the metrics of science to the science of metrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 637-650, February.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:2:d:10.1007_s11192-017-2525-5
    DOI: 10.1007/s11192-017-2525-5
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    References listed on IDEAS

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    1. Gangan Prathap, 2011. "The Energy–Exergy–Entropy (or EEE) sequences in bibliometric assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 515-524, June.
    2. Gangan Prathap, 2011. "Quasity, when quantity has a quality all of its own—toward a theory of performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 555-562, August.
    3. Gangan Prathap, 2010. "Is there a place for a mock h-index?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 153-165, July.
    4. Loet Leydesdorff & Lutz Bornmann, 2011. "Integrated impact indicators compared with impact factors: An alternative research design with policy implications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(11), pages 2133-2146, November.
    5. Philip M. Davis, 2008. "Eigenfactor: Does the principle of repeated improvement result in better estimates than raw citation counts?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(13), pages 2186-2188, November.
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    Citations

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    Cited by:

    1. Federico Caviggioli & Boris Forthmann, 2022. "Reach for the stars: disentangling quantity and quality of inventors’ productivity in a multifaceted latent variable model," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7015-7040, December.
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    3. Belén Payán-Sánchez & Luis Jesús Belmonte-Ureña & José Antonio Plaza-Úbeda & Diego Vazquez-Brust & Natalia Yakovleva & Miguel Pérez-Valls, 2021. "Open Innovation for Sustainability or Not: Literature Reviews of Global Research Trends," Sustainability, MDPI, vol. 13(3), pages 1-29, January.
    4. Prathap, Gangan & Mukherjee, Somenath & Leydesdorff, Loet, 2020. "Within-journal self-citations and the Pinski-Narin influence weights," Journal of Informetrics, Elsevier, vol. 14(1).
    5. Svetla Baykoucheva, 2019. "Eugene Garfield’s Ideas and Legacy and Their Impact on the Culture of Research," Publications, MDPI, vol. 7(2), pages 1-12, June.
    6. Gangan Prathap, 2019. "Scale-dependent stratification: a skyline–shoreline scatter plot," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1269-1273, May.
    7. Yutao Sun & Ying Zhang & Xiaofei Zhang, 2023. "Reconfiguring star inventors with commercialization: a case of the graphene sector," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5411-5440, October.
    8. Gangan Prathap, 2019. "The Pinski–Narin influence weight and the Ramanujacharyulu power-weakness ratio indicators revisited," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1173-1185, May.

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