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Informetric distributions. III. Ambiguity and randomness

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  • A. Bookstein

Abstract

This article examines various kinds of uncertainty. The notion of ambiguity is defined and contrasted with the more familiar notions of randomness and fuzziness. Functional forms resistant to ambiguity are defined, and it is shown how to incorporate a random component, that is itself also resistant to ambiguity, into a resilient, but deterministic, model.

Suggested Citation

  • A. Bookstein, 1997. "Informetric distributions. III. Ambiguity and randomness," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 48(1), pages 2-10, January.
    • Handle: RePEc:bla:jamest:v:48:y:1997:i:1:p:2-10
    DOI: 10.1002/(SICI)1097-4571(199701)48:13.0.CO;2-2
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    File URL: https://doi.org/10.1002/(SICI)1097-4571(199701)48:13.0.CO;2-2
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    Cited by:

    1. Wolfgang Glänzel & Koenraad Debackere, 2022. "Various aspects of interdisciplinarity in research and how to quantify and measure those," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5551-5569, September.
    2. Zahed Bigdeli & Morteza Kokabi & Gholam Reza Rajabi & Ali Gazni, 2013. "Patterns of authors’ information scattering: towards a causal explanation of information scattering from a scholarly information-seeking behavior perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 103-131, July.
    3. Wolfgang Glänzel & Pei-Shan Chi, 2020. "The big challenge of Scientometrics 2.0: exploring the broader impact of scientific research in public health," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1011-1031, November.
    4. Lutz Bornmann & Julian N. Marewski, 2024. "Opium in science and society: numbers and other quantifications," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5313-5346, September.

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