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The skewness of scientific productivity

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  • Ruiz-Castillo, Javier
  • Costas, Rodrigo

Abstract

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.

Suggested Citation

  • Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," UC3M Working papers. Economics we1402, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:werepe:we1402
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    References listed on IDEAS

    as
    1. Ruiz-Castillo Ucelay, Javier & Perianes-Rodríguez, Antonio, 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. repec:spr:scient:v:88:y:2011:i:2:d:10.1007_s11192-011-0407-9 is not listed on IDEAS
    3. 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.
    4. 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, August.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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, June.
    10. 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.
    11. 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, January.
    12. 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.
    13. 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, April.
    14. 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.
    15. 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, January.
    16. 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.
    17. 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.
    18. 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.
    19. 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, May.
    20. 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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    Cited by:

    1. Ruiz-Castillo Ucelay, Javier & Perianes-Rodríguez, Antonio, 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. repec:bla:ecinqu:v:55:y:2017:i:3:p:1308-1323 is not listed on IDEAS
    3. Perlin, Marcelo S. & Santos, André A.P. & Imasato, Takeyoshi & Borenstein, Denis & Da Silva, Sergio, 2017. "The Brazilian scientific output published in journals: A study based on a large CV database," Journal of Informetrics, Elsevier, vol. 11(1), pages 18-31.
    4. Pedro Albarrán & Raquel Carrasco & Javier Ruiz-Castillo, 2017. "Are Migrants More Productive Than Stayers? Some Evidence From A Set Of Highly Productive Academic Economists," Economic Inquiry, Western Economic Association International, vol. 55(3), pages 1308-1323, July.
    5. repec:eee:infome:v:11:y:2017:i:3:p:788-799 is not listed on IDEAS
    6. Gabriel-Alexandru Vîiu & Mihai Păunescu & Adrian Miroiu, 2016. "Research-driven classification and ranking in higher education: an empirical appraisal of a Romanian policy experience," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 785-805, May.
    7. repec:eee:infome:v:11:y:2017:i:2:p:435-454 is not listed on IDEAS
    8. Costas, Rodrigo & Ruiz-Castillo Ucelay, Javier, 2018. "Individual and Field Citation Distributions in 29 Broad Scientific Fields," UC3M Working papers. Economics 26100, Universidad Carlos III de Madrid. Departamento de Economía.
    9. 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.
    10. repec:eee:infome:v:12:y:2018:i:2:p:401-415 is not listed on IDEAS
    11. Antonio Perianes-Rodriguez & Javier Ruiz-Castillo, 2016. "University citation distributions," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(11), pages 2790-2804, November.
    12. Lina M. Cortés & Andrés Mora-Valencia & Javier Perote, 2016. "The productivity of top researchers: a semi-nonparametric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 891-915, November.
    13. repec:spr:scient:v:115:y:2018:i:1:d:10.1007_s11192-018-2644-7 is not listed on IDEAS
    14. Fredrik Niclas Piro & Kristoffer Rørstad & Dag W. Aksnes, 2016. "How does prolific professors influence on the citation impact of their university departments?," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 941-961, June.
    15. Giovanni Abramo & Ciriaco Andrea D’Angelo & Anastasiia Soldatenkova, 2016. "The dispersion of the citation distribution of top scientists’ publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1711-1724, December.
    16. Wolfgang Glänzel & Sarah Heeffer & Bart Thijs, 2016. "A triangular model for publication and citation statistics of individual authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 857-872, May.
    17. Antoine Archambault & Philippe Mongeon & Vincent Larivière, 2017. "On the effects of the reunification on German researchers’ publication patterns," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 337-347, April.
    18. repec:eee:infome:v:11:y:2017:i:3:p:748-765 is not listed on IDEAS
    19. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Soldatenkova, Anastasiia, 2017. "An investigation on the skewness patterns and fractal nature of research productivity distributions at field and discipline level," Journal of Informetrics, Elsevier, vol. 11(1), pages 324-335.
    20. repec:spr:scient:v:102:y:2015:i:2:d:10.1007_s11192-014-1449-6 is not listed on IDEAS
    21. Díaz-Faes, Adrián A. & Costas, Rodrigo & Galindo, M. Purificación & Bordons, María, 2015. "Unravelling the performance of individual scholars: Use of Canonical Biplot analysis to explore the performance of scientists by academic rank and scientific field," Journal of Informetrics, Elsevier, vol. 9(4), pages 722-733.
    22. Kaur, Jasleen & Ferrara, Emilio & Menczer, Filippo & Flammini, Alessandro & Radicchi, Filippo, 2015. "Quality versus quantity in scientific impact," Journal of Informetrics, Elsevier, vol. 9(4), pages 800-808.
    23. Bouyssou, Denis & Marchant, Thierry, 2016. "Ranking authors using fractional counting of citations: An axiomatic approach," Journal of Informetrics, Elsevier, vol. 10(1), pages 183-199.

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