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Average-based versus High- and Low-Impact Indicators for the Evaluation of Scientific Distributions

Author

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  • Ruiz-Castillo, Javier
  • Ortuño-Ortin, Ignacio
  • Albarran, Pedro

Abstract

Albarrán et al. (2009a ) introduced a novel methodology for the evaluation of citation distributions consisting of a pair of high- and a low-impact measures defined over the set of articles with citations below or above a critical citation level CCL. Albarrán et al. (2009b ) presented the first empirical applications to a situation in which the world citation distribution in 22 scientific fields is partitioned into three geographical areas: the U.S., the European Union, and the rest of the world. In this paper, we compare our results with those obtained with average-based indicators. For reasonable CCLs, such as the 80th percentile of the world citation distribution in each field, the cardinal differences between the results obtained with our high-impact index and the mean citation rate are of a large order of magnitude. When, in addition, the percentage in the top 5% of most cited articles or the percentage of uncited articles are used, there are still important quantitative differences with respect to the high- and low-impact indicators advocated in our approach when the CCL is fixed at the 80th or the 95th percentile.

Suggested Citation

  • Ruiz-Castillo, Javier & Ortuño-Ortin, Ignacio & Albarran, Pedro, 2010. "Average-based versus High- and Low-Impact Indicators for the Evaluation of Scientific Distributions," CEPR Discussion Papers 7887, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:7887
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    1. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "The skewness of science in 219 sub-fields and a number of aggregates," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 385-397, August.
    2. Pedro Albarrán & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "Average-based versus high- and low-impact indicators for the evaluation of scientific distributions," Research Evaluation, Oxford University Press, vol. 20(4), pages 325-339, October.
    3. Thed N. Van Leeuwen & Martijn S. Visser & Henk F. Moed & Ton J. Nederhof & Anthony F. J. Van Raan, 2003. "The Holy Grail of science policy: Exploring and combining bibliometric tools in search of scientific excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 57(2), pages 257-280, June.
    4. Albarrán, Pedro & Ortuño, Ignacio & Ruiz-Castillo, Javier, 2011. "The measurement of low- and high-impact in citation distributions: Technical results," Journal of Informetrics, Elsevier, vol. 5(1), pages 48-63.
    5. Robert J. W. Tijssen & Martijn S. Visser & Thed N. van Leeuwen, 2002. "Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference?," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 381-397, July.
    6. Albarrán, Pedro & Crespo, Juan A. & Ortuño, Ignacio & Ruiz-Castillo, Javier, 2009. "A comparison of the scientific performance of the U. S. and the European Union at the turn of the XXI century," UC3M Working papers. Economics we095534, Universidad Carlos III de Madrid. Departamento de Economía.
    7. Wolfgang Glänzel & András Schubert & Tibor Braun, 2002. "A relational charting approach to the world of basic research in twelve science fields at the end of the second millennium," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(3), pages 335-348, November.
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    1. Albarrán, Pedro & Herrero, Carmen & Ruiz-Castillo, Javier & Villar, Antonio, 2017. "The Herrero-Villar approach to citation impact," Journal of Informetrics, Elsevier, vol. 11(2), pages 625-640.
    2. Pedro Albarrán & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "Average-based versus high- and low-impact indicators for the evaluation of scientific distributions," Research Evaluation, Oxford University Press, vol. 20(4), pages 325-339, October.
    3. Herranz, Neus & Ruiz-Castillo, Javier, 2012. "Sub-field normalization in the multiplicative case: Average-based citation indicators," Journal of Informetrics, Elsevier, vol. 6(4), pages 543-556.
    4. Neus Herranz & Javier Ruiz-Castillo, 2013. "The end of the “European Paradox”," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 453-464, April.
    5. Javier Ruiz-Castillo, 2012. "The evaluation of citation distributions," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(1), pages 291-310, March.
    6. Andrea Bonaccorsi & Tindaro Cicero & Peter Haddawy & Saeed-UL Hassan, 2017. "Explaining the transatlantic gap in research excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 217-241, January.
    7. Bonaccorsi, Andrea & Haddawy, Peter & Cicero, Tindaro & Hassan, Saeed-Ul, 2017. "The solitude of stars. An analysis of the distributed excellence model of European universities," Journal of Informetrics, Elsevier, vol. 11(2), pages 435-454.
    8. Brito, Ricardo & Rodríguez-Navarro, Alonso, 2018. "Research assessment by percentile-based double rank analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 315-329.
    9. Tomaz Bartol & Gordana Budimir & Primoz Juznic & Karmen Stopar, 2016. "Mapping and classification of agriculture in Web of Science: other subject categories and research fields may benefit," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 979-996, November.

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    More about this item

    Keywords

    Citation distributions; Measuring scientific performance;

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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