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Informetric distributions, part I: Unified overview

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  • A. Bookstein

Abstract

This article is the first of a two‐part series on the informetric distributions, a family of regularities found to describe a wide range of phenomena both within and outside of the information sciences. This article introduces the basic forms these regularities take. A model is proposed that makes plausible the possibility that, in spite of marked differences in their appearance, these distributions are variants of a single distribution; heuristic arguments are then given that this is indeed the case. That a single distribution should describe such a wide range of phenomena, often in areas where the existence of any simple description is surprising, suggests that one should look for explanations not in terms of causal models, but in terms of the properties of the single informetric distribution. Some of the consequences of this conclusion are broached in this article, and explored more carefully in Part II. © 1990 John Wiley & Sons, Inc.

Suggested Citation

  • A. Bookstein, 1990. "Informetric distributions, part I: Unified overview," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(5), pages 368-375, July.
  • Handle: RePEc:bla:jamest:v:41:y:1990:i:5:p:368-375
    DOI: 10.1002/(SICI)1097-4571(199007)41:53.0.CO;2-C
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    Cited by:

    1. Dimosthenis Kifokeris & Yiannis Xenidis, 2021. "Game Theory-Based Minimization of the Ostracism Risk in Construction Companies," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    2. Heinrich Behrens & Peter Luksch, 2011. "Mathematics 1868–2008: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 179-194, January.
    3. Dirk Lewandowski, 2015. "Evaluating the retrieval effectiveness of web search engines using a representative query sample," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(9), pages 1763-1775, September.

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