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Quantifying the scientific output of new researchers using the zp-index

Author

Listed:
  • Christopher Zou

    (University of Toronto)

  • Jordan B. Peterson

    (University of Toronto)

Abstract

Despite a high level of interest in quantifying the scientific output of established researchers, there has been less of a focus on quantifying the performance of junior researchers. The available metrics that quantify a scientist’s research output all utilize citation information, which often takes a number of years to accrue and thus would disadvantage newer researchers (e.g., graduate students, post-doctoral members, new professors). Based on this critical limitation of existing metrics, we created a new metric of scientific output, the zp-index, which remedies this issue by utilizing the journal quality rather than citation count in calculating an index of scientific output. Additionally, the zp-index also takes authorship position into account by allocating empirically derived weights to each authorship position, so that first authorship publications receive more credit than later authorship positions (Study 1). Furthermore, the zp-index has equal predictive validity as a measure of the number of publications but does a better job of discriminating researcher’s scientific output and may provide different information than the number of publications (Study 2). Therefore, use of the zp-index in conjunction with the number of publications can provide a more accurate assessment of a new scientist’s academic achievements.

Suggested Citation

  • Christopher Zou & Jordan B. Peterson, 2016. "Quantifying the scientific output of new researchers using the zp-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 901-916, March.
    • Handle: RePEc:spr:scient:v:106:y:2016:i:3:d:10.1007_s11192-015-1807-z
    DOI: 10.1007/s11192-015-1807-z
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    References listed on IDEAS

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    Cited by:

    1. Christopher Zou & Julia Tsui & Jordan B. Peterson, 2018. "The publication trajectory of graduate students, post-doctoral fellows, and new professors in psychology," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1289-1310, November.
    2. Dosso, Dennis & Silvello, Gianmaria, 2020. "Data credit distribution: A new method to estimate databases impact," Journal of Informetrics, Elsevier, vol. 14(4).

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