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A quantitative analysis of indicators of scientific performance

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Abstract

Condensing the work of any academic scientist into a one-dimensional indicator of scientific performance is a difficult problem. Here, we employ Bayesian statistics to analyze several different indicators of scientific performance. Specifically, we determine each indicator’s ability to discriminate between scientific authors. Using scaling arguments, we demonstrate that the best of these indicators require approximately 50 papers to draw conclusions regarding long term scientific performance with usefully small statistical uncertainties. Further, the approach described here permits statistical comparison of scientists working in distinct areas of science.

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Authors and Affiliations

  1. Center for Complex Network Research, Department of Physics, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA

    Sune Lehmann

  2. Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard University, Boston, USA

    Sune Lehmann

  3. The Niels Bohr Institute, Copenhagen, Denmark

    Andrew D. Jackson & Benny E. Lautrup

Authors
  1. Sune Lehmann
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  2. Andrew D. Jackson
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  3. Benny E. Lautrup
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Correspondence to Sune Lehmann.

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Lehmann, S., Jackson, A.D. & Lautrup, B.E. A quantitative analysis of indicators of scientific performance. Scientometrics 76, 369–390 (2008). https://doi.org/10.1007/s11192-007-1868-8

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  • DOI: https://doi.org/10.1007/s11192-007-1868-8

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