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The skewness of scientific productivity

Listed author(s):
  • Costas, Rodrigo
  • Ruiz-Castillo, Javier

This paper exploits a unique 2003-2011 large dataset, indexed by Thomson & Reuters, consisting of 17.2 million disambiguated authors classified into 30 broad scientific fields, as well as the 48.2 million articles resulting from a multiplying strategy in which any article co-authored by two or more persons is wholly assigned as many times as necessary to each of them. The dataset is characterized by a large proportion of authors who have their oeuvre in several fields. We measure individual productivity in two ways that are uncorrelated: as the number of articles per person, and as the mean citation per article per person in the 2003-2011 period. We analyze the shape of the two types of individual productivity distributions in each field using size- and scale-independent indicators. For productivity inequality, we use the coefficient of variation. To assess the skewness of productivity distributions we use a robust index of skeweness, as well as the Characteristic Scores and Scales approach. For productivity inequality, we use the coefficient of variation. In each field, we study two samples: the entire population, and what we call “successful authors”, namely, the subset of scientists whose productivity is above their field average. The main result is that, in spite of wide differences in production and citation practices across fields, the shape of field productivity distributions are very similar across fields. The parallelism of the results for the population as a whole and for the subset of successful authors when productivity is measured as mean citation per article per person, reveals the fractal nature of the skewness of scientific productivity in this case. These results are essentially maintained when any article co-authored by two or more persons is fractionally assigned to each of them.

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File URL: http://e-archivo.uc3m.es/bitstream/handle/10016/18286/we1402.pdf?sequence=1
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Paper provided by Universidad Carlos III de Madrid. Departamento de Economía in its series UC3M Working papers. Economics with number we1402.

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Date of creation: 01 Jan 2014
Handle: RePEc:cte:werepe:we1402
Contact details of provider: Web page: http://www.eco.uc3m.es/

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  1. Perianes-Rodríguez, Antonio & Ruiz-Castillo Ucelay, Javier, 2014. "Within and across department variability in individual productivity : the case of economics," UC3M Working papers. Economics we1404, Universidad Carlos III de Madrid. Departamento de Economía.
  2. Neus Herranz & Javier Ruiz-Castillo, 2012. "Sub-field normalization in the multiplicative case: High- and low-impact citation indicators," Research Evaluation, Oxford University Press, vol. 21(2), pages 113-125, April.
  3. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, 08.
  4. 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.
  5. Waltman, Ludo & van Eck, Nees Jan, 2013. "A systematic empirical comparison of different approaches for normalizing citation impact indicators," Journal of Informetrics, Elsevier, vol. 7(4), pages 833-849.
  6. Neus Herranz & Javier Ruiz-Castillo, 2012. "Multiplicative and fractional strategies when journals are assigned to several subfields," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2195-2205, November.
  7. Yunrong Li & Javier Ruiz-Castillo, 2014. "The impact of extreme observations in citation distributions," Research Evaluation, Oxford University Press, vol. 23(2), pages 174-182.
  8. Juan A. Crespo & Neus Herranz & Yunrong Li & Javier Ruiz-Castillo, 2014. "The effect on citation inequality of differences in citation practices at the web of science subject category level," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(6), pages 1244-1256, 06.
  9. 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.
  10. 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.
  11. Jarno Hoekman & Thomas Scherngell & Koen Frenken & Robert Tijssen, 2013. "Acquisition of European research funds and its effect on international scientific collaboration," Journal of Economic Geography, Oxford University Press, vol. 13(1), pages 23-52, January.
  12. Kevin W. Boyack & Richard Klavans, 2014. "Creation of a highly detailed, dynamic, global model and map of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 670-685, 04.
  13. Li, Yunrong & Radicchi, Filippo & Castellano, Claudio & Ruiz-Castillo, Javier, 2013. "Quantitative evaluation of alternative field normalization procedures," Journal of Informetrics, Elsevier, vol. 7(3), pages 746-755.
  14. Ludo Waltman & Nees Jan van Eck & Anthony F. J. van Raan, 2012. "Universality of citation distributions revisited," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 72-77, 01.
  15. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
  16. Buter, R.K. & van Raan, A.F.J., 2011. "Non-alphanumeric characters in titles of scientific publications: An analysis of their occurrence and correlation with citation impact," Journal of Informetrics, Elsevier, vol. 5(4), pages 608-617.
  17. Hoekman, Jarno & Frenken, Koen & Tijssen, Robert J.W., 2010. "Research collaboration at a distance: Changing spatial patterns of scientific collaboration within Europe," Research Policy, Elsevier, vol. 39(5), pages 662-673, June.
  18. Michael Levin & Stefan Krawczyk & Steven Bethard & Dan Jurafsky, 2012. "Citation-based bootstrapping for large-scale author disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(5), pages 1030-1047, 05.
  19. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
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