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The effects and their stability of field normalization baseline on relative performance with respect to citation impact: A case study of 20 natural science departments

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  • Colliander, Cristian
  • Ahlgren, Per

Abstract

In this paper we study the effects of field normalization baseline on relative performance of 20 natural science departments in terms of citation impact. Impact is studied under three baselines: journal, ISI/Thomson Reuters subject category, and Essential Science Indicators field. For the measurement of citation impact, the indicators item-oriented mean normalized citation rate and Top-5% are employed. The results, which we analyze with respect to stability, show that the choice of normalization baseline matters. We observe that normalization against publishing journal is particular. The rankings of the departments obtained when journal is used as baseline, irrespective of indicator, differ considerably from the rankings obtained when ISI/Thomson Reuters subject category or Essential Science Indicators field is used. Since no substantial differences are observed when the baselines Essential Science Indicators field and ISI/Thomson Reuters subject category are contrasted, one might suggest that people without access to subject category data can perform reasonable normalized citation impact studies by combining normalization against journal with normalization against Essential Science Indicators field.

Suggested Citation

  • Colliander, Cristian & Ahlgren, Per, 2011. "The effects and their stability of field normalization baseline on relative performance with respect to citation impact: A case study of 20 natural science departments," Journal of Informetrics, Elsevier, vol. 5(1), pages 101-113.
    • Handle: RePEc:eee:infome:v:5:y:2011:i:1:p:101-113
    DOI: 10.1016/j.joi.2010.09.003
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    5. Schneider, Jesper W., 2013. "Caveats for using statistical significance tests in research assessments," Journal of Informetrics, Elsevier, vol. 7(1), pages 50-62.
    6. Ruiz-Castillo, Javier & Waltman, Ludo, 2015. "Field-normalized citation impact indicators using algorithmically constructed classification systems of science," Journal of Informetrics, Elsevier, vol. 9(1), pages 102-117.
    7. Cinzia Daraio & Simone Di Leo & Loet Leydesdorff, 2023. "A heuristic approach based on Leiden rankings to identify outliers: evidence from Italian universities in the European landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 483-510, January.
    8. Hu, Zhigang & Tian, Wencan & Xu, Shenmeng & Zhang, Chunbo & Wang, Xianwen, 2018. "Four pitfalls in normalizing citation indicators: An investigation of ESI’s selection of highly cited papers," Journal of Informetrics, Elsevier, vol. 12(4), pages 1133-1145.
    9. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "On the interplay between normalisation, bias, and performance of paper impact metrics," Journal of Informetrics, Elsevier, vol. 13(1), pages 270-290.
    10. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    11. Ludo Waltman & Michael Schreiber, 2013. "On the calculation of percentile-based bibliometric indicators," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(2), pages 372-379, February.
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    13. Pislyakov, Vladimir, 2022. "On some properties of medians, percentiles, baselines, and thresholds in empirical bibliometric analysis," Journal of Informetrics, Elsevier, vol. 16(4).
    14. Cinzia Daraio & Simone Di Leo & Loet Leydesdorff, 2022. "Using the Leiden Rankings as a Heuristics: Evidence from Italian universities in the European landscape," LEM Papers Series 2022/08, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    15. Ludo Waltman & Nees Jan Eck & Thed N. Leeuwen & Martijn S. Visser & Anthony F. J. Raan, 2011. "Towards a new crown indicator: an empirical analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 467-481, June.
    16. Vaccario, Giacomo & Medo, Matúš & Wider, Nicolas & Mariani, Manuel Sebastian, 2017. "Quantifying and suppressing ranking bias in a large citation network," Journal of Informetrics, Elsevier, vol. 11(3), pages 766-782.

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