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Patterns of Scientific Productivity and Social Change: A Discussion of Lotka's Law and Bibliometric Symmetry

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  • Abraham Bookstein

Abstract

This paper examines the application of symmetry principles to bibliometric laws, using Lotka's law for illustration. A general model describing scientific productivity is defined and modified to be consistent with a generalized form of Lotka's law; the model in this form is shown to be stable with regard to at least two forms of social change. Then the consequences of invariance under change of time span are investigated, and it is shown that the function occurring in Lotka's law, with an arbitrary exponent, is essentially the only one with desireable properties that is consistent with the symmetry constraint.

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  • Abraham Bookstein, 1977. "Patterns of Scientific Productivity and Social Change: A Discussion of Lotka's Law and Bibliometric Symmetry," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 28(4), pages 206-210, July.
  • Handle: RePEc:bla:jamest:v:28:y:1977:i:4:p:206-210
    DOI: 10.1002/asi.1977.28.4.206
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    Cited by:

    1. Debabrata Talukdar, 2011. "Patterns of Research Productivity in the Business Ethics Literature: Insights from Analyses of Bibliometric Distributions," Journal of Business Ethics, Springer, vol. 98(1), pages 137-151, January.
    2. Zornig, Peter & Altmann, Gabriel, 1995. "Unified representation of Zipf distributions," Computational Statistics & Data Analysis, Elsevier, vol. 19(4), pages 461-473, April.
    3. Vincenzo Basile & Massimiliano Giacalone & Paolo Carmelo Cozzucoli, 2022. "The Impacts of Bibliometrics Measurement in the Scientific Community A Statistical Analysis of Multiple Case Studies," Review of European Studies, Canadian Center of Science and Education, vol. 14(3), pages 1-10, November.
    4. Sarabia, José María & Gómez-Déniz, Emilio & Sarabia, María & Prieto, Faustino, 2010. "A general method for generating parametric Lorenz and Leimkuhler curves," Journal of Informetrics, Elsevier, vol. 4(4), pages 524-539.

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