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The measurement of low- and high-impact in citation distributions : technical results

Listed author(s):
  • Albarrán, Pedro
  • Ruiz-Castillo, Javier
  • Ortuño, Ignacio

This paper introduces a novel methodology for comparing the citation distributions of research units working in the same homogeneous field. Given a critical citation level (CCL), we suggest using two real valued indicators to describe the shape of any distribution: a high-impact and a low-impact measure defined over the set of articles with citations above or below the CCL. The key to this methodology is the identification of a citation distribution with an income distribution. Once this step is taken, it is easy to realize that the measurement of low-impact coincides with the measurement of economic poverty. In turn, it is equally natural to identify the measurement of high-impact with the measurement of a certain notion of economic affluence. On the other hand, it is seen that the ranking of citation distributions according to a family of low-impact measures is essentially characterized by a number of desirable axioms. Appropriately redefined, these same axioms lead to the selection of an equally convenient class of decomposable high-impact measures. These two families are shown to satisfy other interesting properties that make them potentially useful in empirical applications, including the comparison of research units working in different fields.

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Paper provided by Universidad Carlos III de Madrid. Departamento de Economía in its series UC3M Working papers. Economics with number we095735.

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Date of creation: Dec 2009
Handle: RePEc:cte:werepe:we095735
Contact details of provider: Web page: http://www.eco.uc3m.es/

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  1. Albarrán, Pedro & Ruiz-Castillo, Javier & Ortuño, Ignacio & Crespo, Juan A., 2010. "The skewness of science in 219 sub-fields and a number of aggregates," UC3M Working papers. Economics we1038, Universidad Carlos III de Madrid. Departamento de Economía.
  2. Zheng, Buhong, 1997. " Aggregate Poverty Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 11(2), pages 123-162, June.
  3. 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.
  4. Pedro Albarrán & Javier Ruiz-Castillo, 2011. "References made and citations received by scientific articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(1), pages 40-49, 01.
  5. 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.
  6. Katz, J. Sylvan, 1999. "The self-similar science system1," Research Policy, Elsevier, vol. 28(5), pages 501-517, June.
  7. Woeginger, Gerhard J., 2008. "An axiomatic characterization of the Hirsch-index," Mathematical Social Sciences, Elsevier, vol. 56(2), pages 224-232, September.
  8. Clark, Stephen & Hemming, Richard & Ulph, David, 1981. "On Indices for the Measurement of Poverty," Economic Journal, Royal Economic Society, vol. 91(362), pages 515-526, June.
  9. Jenkins, Stephen P & Lambert, Peter J, 1997. "Three 'I's of Poverty Curves, with an Analysis of UK Poverty Trends," Oxford Economic Papers, Oxford University Press, vol. 49(3), pages 317-327, July.
  10. Dasgupta, Partha & Sen, Amartya & Starrett, David, 1973. "Notes on the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 6(2), pages 180-187, April.
  11. J Sylvan Katz, 2000. "Scale-independent indicators and research evaluation," Science and Public Policy, Oxford University Press, vol. 27(1), pages 23-36, February.
  12. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
  13. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
  14. Thon, Dominique, 1979. "On Measuring Poverty," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 25(4), pages 429-439, December.
  15. Woeginger, Gerhard J., 2008. "A symmetry axiom for scientific impact indices," Journal of Informetrics, Elsevier, vol. 2(4), pages 298-303.
  16. Quesada, Antonio, 2009. "Monotonicity and the Hirsch index," Journal of Informetrics, Elsevier, vol. 3(2), pages 158-160.
  17. David Johnson, 1988. "The Measurement of Poverty in Australia: 1981-82 and 1985-86," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 21(3), pages 13-24.
  18. Martin, Ben R. & Irvine, John, 1983. "Assessing basic research : Some partial indicators of scientific progress in radio astronomy," Research Policy, Elsevier, vol. 12(2), pages 61-90, April.
  19. Chakravarty, Satya R., 1983. "A new index of poverty," Mathematical Social Sciences, Elsevier, vol. 6(3), pages 307-313, December.
  20. Foster, James E & Shorrocks, Anthony F, 1991. "Subgroup Consistent Poverty Indices," Econometrica, Econometric Society, vol. 59(3), pages 687-709, May.
  21. Pyatt, Graham, 1987. "Measuring Welfare, Poverty and Inequality," Economic Journal, Royal Economic Society, vol. 97(386), pages 459-467, June.
  22. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-231, March.
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