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The evaluation of citation distributions

  • Javier Ruiz-Castillo


This paper reviews a number of recent contributions that demonstrate that a blend of welfare economics and statistical analysis is useful in the evaluation of the citations received by scientific papers in the periodical literature. The paper begins by clarifying the role of citation analysis in the evaluation of research. Next, a summary of results about the citation distributions’ basic features at different aggregation levels is offered. These results indicate that citation distributions share the same broad shape, are highly skewed, and are often crowned by a power law. In light of this evidence, a novel methodology for the evaluation of research units is illustrated by comparing the high- and low-citation impact achieved by the U.S., the European Union, and the rest of the world in 22 scientific fields. However, contrary to recent claims, it is shown that mean normalization at the sub-field level does not lead to a universal distribution. Nevertheless, among other topics subject to ongoing research, it appears that this lack of universality does not preclude sensible normalization procedures to compare the citation impact of articles in different scientific fields.

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Article provided by Spanish Economic Association in its journal SERIEs.

Volume (Year): 3 (2012)
Issue (Month): 1 (March)
Pages: 291-310

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Handle: RePEc:spr:series:v:3:y:2012:i:1:p:291-310
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  1. Albarrán, Pedro & Ortuño, Ignacio & Ruiz-Castillo, Javier, 2011. "High- and low-impact citation measures: Empirical applications," Journal of Informetrics, Elsevier, vol. 5(1), pages 122-145.
  2. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-31, March.
  3. Woeginger, Gerhard J., 2008. "A symmetry axiom for scientific impact indices," Journal of Informetrics, Elsevier, vol. 2(4), pages 298-303.
  4. Pedro Albarrán & Joan Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2009. "A comparison of the scientific performance of the U. S. and the European Union at the turn of the XXI century," Economics Working Papers we095534, Universidad Carlos III, Departamento de Economía.
  5. Giovanni Dosi & Patrick Llerena & Mauro Sylos Labini, 2005. "Science-Technology-Industry Links and the ”European Paradox”: Some Notes on the Dynamics of Scientific and Technological Research in Europe," LEM Papers Series 2005/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  6. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "The skewness of science in 219 sub-fields and a number of aggregates," Economics Working Papers we1109, Universidad Carlos III, Departamento de Economía.
  7. Woeginger, Gerhard J., 2008. "An axiomatic characterization of the Hirsch-index," Mathematical Social Sciences, Elsevier, vol. 56(2), pages 224-232, September.
  8. Moed, H. F. & Burger, W. J. M. & Frankfort, J. G. & Van Raan, A. F. J., 1985. "The use of bibliometric data for the measurement of university research performance," Research Policy, Elsevier, vol. 14(3), pages 131-149, June.
  9. Quesada, Antonio, 2009. "Monotonicity and the Hirsch index," Journal of Informetrics, Elsevier, vol. 3(2), pages 158-160.
  10. Pedro Albarran & Ignacio Ortuno & Javier Ruiz-Castillo, 2009. "The measurement of low- and high-impact in citation distributions: technical results," Economics Working Papers we095735, Universidad Carlos III, Departamento de Economía.
  11. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-66, May.
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  13. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
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