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The law of limited excellence: publication productivity of Israel Prize laureates in the life and exact sciences

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  • Gad Yair

    (Hebrew University of Jerusalem)

  • Nofar Gueta

    (Hebrew University of Jerusalem)

  • Nitza Davidovitch

    (Ariel University)

Abstract

The present paper extends Lotka’s theorem—which we rename as “the law of limited excellence”—while empirically modelling the scientific productivity of 46 Israel Prize laureates in the life and exact sciences—a group best described as ‘Star Scientists’. By focusing on this highly selective group we expose unequal scientific productivity even amongst Israel’s most prolific scientists. Specifically, we test the invariance of Lotka’s law by focusing attention on the extreme tail of publication distributions while empirically exploring the non-linearity of its seemingly “flat” tail. By exposing the rarity of excellence even in this extreme end of publication productivity we extend the generality of Lotka’s theorem and expose that—like a fractal—the tail of excellence behaves as the entire distribution. We end this empirical contribution by suggesting a few implications for research and policy.

Suggested Citation

  • Gad Yair & Nofar Gueta & Nitza Davidovitch, 2017. "The law of limited excellence: publication productivity of Israel Prize laureates in the life and exact sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 299-311, October.
  • Handle: RePEc:spr:scient:v:113:y:2017:i:1:d:10.1007_s11192-017-2465-0
    DOI: 10.1007/s11192-017-2465-0
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    References listed on IDEAS

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    1. Garfield, Eugene, 2009. "From the science of science to Scientometrics visualizing the history of science with HistCite software," Journal of Informetrics, Elsevier, vol. 3(3), pages 173-179.
    2. L Egghe, 2005. "Relations between the continuous and the discrete Lotka power function," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(7), pages 664-668, May.
    3. Per O. Seglen, 1992. "The skewness of science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 628-638, October.
    4. Lorenzo Ductor, 2015. "Does Co-authorship Lead to Higher Academic Productivity?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 385-407, June.
    5. Peter James Bentley, 2015. "Cross-country differences in publishing productivity of academics in research universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 865-883, January.
    6. Giovanni Abramo & Ciriaco Andrea D’Angelo & Alessandro Caprasecca, 2009. "The contribution of star scientists to overall sex differences in research productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 137-156, October.
    7. Juntao Zheng & Niancai Liu, 2015. "Mapping of important international academic awards," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 763-791, September.
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    Cited by:

    1. Gad Yair & Keith Goldstein & Nir Rotem & Anthony J. Olejniczak, 2022. "The three cultures in American science: publication productivity in physics, history and economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 2967-2980, June.
    2. Yu-Wei Chang & Dar-Zen Chen & Mu-Hsuan Huang, 2020. "Discovering types of research performance of scientists with significant contributions," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1529-1552, August.
    3. Gad Yair & Keith Goldstein, 2020. "The Annus Mirabilis paper: years of peak productivity in scientific careers," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 887-902, August.
    4. Maor Weinberger & Maayan Zhitomirsky-Geffet, 2021. "Diversity of success: measuring the scholarly performance diversity of tenured professors in the Israeli academia," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2931-2970, April.
    5. Creso Sá & Summer Cowley & Magdalena Martinez & Nadiia Kachynska & Emma Sabzalieva, 2020. "Gender gaps in research productivity and recognition among elite scientists in the U.S., Canada, and South Africa," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
    6. Eyal Eckhaus & Nitza Davidovitch, 2021. "Academic Rank and Position Effect on Academic Research Output – A Case Study of Ariel University," International Journal of Higher Education, Sciedu Press, vol. 10(1), pages 295-295, February.
    7. Marek Kwiek, 2018. "High research productivity in vertically undifferentiated higher education systems: Who are the top performers?," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 415-462, April.
    8. Fan Jiang & Niancai Liu, 2018. "The hierarchical status of international academic awards in social sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 2091-2115, December.
    9. Basma Albanna & Julia Handl & Richard Heeks, 2021. "Publication outperformance among global South researchers: An analysis of individual-level and publication-level predictors of positive deviance," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8375-8431, October.

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