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A mathematical approach to assess research diversity: operationalization and applicability in communication sciences, political science, and beyond

Author

Listed:
  • Manuel Goyanes

    (Carlos III University
    University of Salamanca)

  • Márton Demeter

    (National University of Public Service)

  • Aurea Grané

    (Universidad Carlos III de Madrid)

  • Irene Albarrán-Lozano

    (Universidad Carlos III de Madrid)

  • Homero Gil de Zúñiga

    (University of Salamanca
    Pennsylvania State University
    Universidad Diego Portales)

Abstract

With today’s research production and global dissemination, there is growing pressure to assess how academic fields foster diversity. Based on a mathematical problem/solve scheme, the aim of this study is twofold. First, the paper elaborates on how research diversity in scientific fields can be empirically gauged, proposing six working definitions. Second, drawing on these theoretical explanations, we introduce an original methodological protocol for research diversity evaluation. Third, the study puts this mathematical model to an empirical test by comparatively evaluating (1) communication research diversity in 2017, with respect to field’s diversity in 1997, and (2) communication research and political science diversity in 2017. Our results indicate that, contrasted to pattern diversity, communication research in 2017 is not a diverse field. However, throughout the years (1997–2017), there is a statistically significant improvement. Finally, the cross-comparison examination between political and communication sciences reveals the latter to be significantly more diverse.

Suggested Citation

  • Manuel Goyanes & Márton Demeter & Aurea Grané & Irene Albarrán-Lozano & Homero Gil de Zúñiga, 2020. "A mathematical approach to assess research diversity: operationalization and applicability in communication sciences, political science, and beyond," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2299-2322, December.
  • Handle: RePEc:spr:scient:v:125:y:2020:i:3:d:10.1007_s11192-020-03680-6
    DOI: 10.1007/s11192-020-03680-6
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    References listed on IDEAS

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    1. Lin Zhang & Wolfgang Glänzel & Liming Liang, 2009. "Tracing the role of individual journals in a cross-citation network based on different indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 821-838, December.
    2. Frédérique Bone & Michael M. Hopkins & Ismael Ràfols & Jordi Molas-Gallart & Puay Tang & Gail Davey & Antony M. Carr, 2019. "DARE to be different? Applying diversity indicators to the evaluation of collaborative research projects," SPRU Working Paper Series 2019-09, SPRU - Science Policy Research Unit, University of Sussex Business School.
    3. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    4. Lin Zhang & Frizo Janssens & Liming Liang & Wolfgang Glänzel, 2010. "Journal cross-citation analysis for validation and improvement of journal-based subject classification in bibliometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 687-706, March.
    5. Lin Zhang & Ronald Rousseau & Wolfgang Glänzel, 2016. "Diversity of references as an indicator of the interdisciplinarity of journals: Taking similarity between subject fields into account," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1257-1265, May.
    6. Han Woo Park & Loet Leydesdorff, 2009. "Knowledge linkage structures in communication studies using citation analysis among communication journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 157-175, October.
    7. Alpa Dhanani & Michael John Jones, 2017. "Editorial boards of accounting journals: gender diversity and internationalisation," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 30(5), pages 1008-1040, June.
    8. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
    9. Loet Leydesdorff & Carole Probst, 2009. "The delineation of an interdisciplinary specialty in terms of a journal set: The case of communication studies," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(8), pages 1709-1718, August.
    10. Darrin J. Griffin & San Bolkan & Jennifer L. Holmgren & Frank Tutzauer, 2016. "Central journals and authors in communication using a publication network," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 91-104, January.
    11. Sungbin Youk & Hee Sun Park, 2019. "Where and what do they publish? Editors’ and editorial board members’ affiliated institutions and the citation counts of their endogenous publications in the field of communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1237-1260, September.
    12. Leydesdorff, Loet & Wagner, Caroline S. & Bornmann, Lutz, 2019. "Interdisciplinarity as diversity in citation patterns among journals: Rao-Stirling diversity, relative variety, and the Gini coefficient," Journal of Informetrics, Elsevier, vol. 13(1), pages 255-269.
    13. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
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    Cited by:

    1. Manuel Goyanes & Márton Demeter & Zicheng Cheng & Homero Gil Zúñiga, 2022. "Measuring publication diversity among the most productive scholars: how research trajectories differ in communication, psychology, and political science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3661-3682, June.
    2. Rüdiger Mutz, 2022. "Diversity and interdisciplinarity: Should variety, balance and disparity be combined as a product or better as a sum? An information-theoretical and statistical estimation approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7397-7414, December.

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