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An empirical investigation of the tribes and their territories: Are research specialisms rural and urban?

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  • Colavizza, Giovanni
  • Franssen, Thomas
  • van Leeuwen, Thed

Abstract

We propose an operationalization of the rural and urban analogy introduced in Becher and Trowler (2001). According to them, a specialism is rural if it is organized into many, smaller topics of research, with higher author mobility among them, lower rate of collaboration and productivity, lower competition for resources and citation recognitions compared to an urban specialism. It is assumed that most humanities specialisms are rural while science specialisms are in general urban: we set to test this hypothesis empirically. We first propose an operationalization of the theory in most of its quantifiable aspects. We then consider specialisms from history, literature, computer science, biology, astronomy. Our results show that specialisms in the humanities present a sensibly lower citation and textual connectivity, in agreement with their organization into more, smaller topics per specialism, as suggested by the analogy. We argue that the intellectual organization of rural specialisms might indeed be qualitative different from urban ones, discouraging the straightforward application of citation-based indicators commonly applied to urban specialisms without a dedicated re-design in acknowledgement of these differences.

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  • Colavizza, Giovanni & Franssen, Thomas & van Leeuwen, Thed, 2019. "An empirical investigation of the tribes and their territories: Are research specialisms rural and urban?," Journal of Informetrics, Elsevier, vol. 13(1), pages 105-117.
  • Handle: RePEc:eee:infome:v:13:y:2019:i:1:p:105-117
    DOI: 10.1016/j.joi.2018.11.006
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    References listed on IDEAS

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    1. Giovanni Colavizza & Kevin W. Boyack & Nees Jan van Eck & Ludo Waltman, 2018. "The Closer the Better: Similarity of Publication Pairs at Different Cocitation Levels," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(4), pages 600-609, April.
    2. Emanuel Kulczycki & Tim C. E. Engels & Janne Pölönen & Kasper Bruun & Marta Dušková & Raf Guns & Robert Nowotniak & Michal Petr & Gunnar Sivertsen & Andreja Istenič Starčič & Alesia Zuccala, 2018. "Publication patterns in the social sciences and humanities: evidence from eight European countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 463-486, July.
    3. Anne-Wil Harzing & Satu Alakangas, 2016. "Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 787-804, February.
    4. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    5. Loet Leydesdorff & Björn Hammarfelt & Almila Salah, 2011. "The structure of the Arts & Humanities Citation Index: A mapping on the basis of aggregated citations among 1,157 journals," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(12), pages 2414-2426, December.
    6. Chin-Chang Tsai & Elizabeth A. Corley & Barry Bozeman, 2016. "Collaboration experiences across scientific disciplines and cohorts," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 505-529, August.
    7. Mathieu Jacomy & Tommaso Venturini & Sebastien Heymann & Mathieu Bastian, 2014. "ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-12, June.
    8. Thed N. Leeuwen & Erik Wijk & Paul F. Wouters, 2016. "Bibliometric analysis of output and impact based on CRIS data: a case study on the registered output of a Dutch university," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 1-16, January.
    9. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    10. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
    11. Vincent Larivière & Éric Archambault & Yves Gingras, 2008. "Long‐term variations in the aging of scientific literature: From exponential growth to steady‐state science (1900–2004)," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(2), pages 288-296, January.
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