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Average-based versus high- and low-impact indicators for the evaluation of scientific distributions

Author

Listed:
  • Pedro Albarrán
  • Ignacio Ortuño
  • Javier Ruiz-Castillo

Abstract

Albarrán et al (2009a) introduced a novel methodology for the evaluation of citation distributions using a pair of high- and low-impact measures defined over the set of articles with citations below or above a critical citation level. 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 USA, the European Union, and the rest of the world. In this paper, we find that 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. Copyright , Beech Tree Publishing.

Suggested Citation

  • 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.
    • Handle: RePEc:oup:rseval:v:20:y:2011:i:4:p:325-339
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    Cited by:

    1. 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.
    2. 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.
    3. Brito, Ricardo & Rodríguez-Navarro, Alonso, 2018. "Research assessment by percentile-based double rank analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 315-329.
    4. 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.
    5. Neus Herranz & Javier Ruiz-Castillo, 2013. "The end of the “European Paradox”," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 453-464, April.
    6. 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.
    7. 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.
    8. 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.
    9. 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.

    More about this item

    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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