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Bibliometric Evidence for a Hierarchy of the Sciences

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  • Daniele Fanelli
  • Wolfgang Glänzel

Abstract

The hypothesis of a Hierarchy of the Sciences, first formulated in the 19th century, predicts that, moving from simple and general phenomena (e.g. particle dynamics) to complex and particular (e.g. human behaviour), researchers lose ability to reach theoretical and methodological consensus. This hypothesis places each field of research along a continuum of complexity and “softness”, with profound implications for our understanding of scientific knowledge. Today, however, the idea is still unproven and philosophically overlooked, too often confused with simplistic dichotomies that contrast natural and social sciences, or science and the humanities. Empirical tests of the hypothesis have usually compared few fields and this, combined with other limitations, makes their results contradictory and inconclusive. We verified whether discipline characteristics reflect a hierarchy, a dichotomy or neither, by sampling nearly 29,000 papers published contemporaneously in 12 disciplines and measuring a set of parameters hypothesised to reflect theoretical and methodological consensus. The biological sciences had in most cases intermediate values between the physical and the social, with bio-molecular disciplines appearing harder than zoology, botany or ecology. In multivariable analyses, most of these parameters were independent predictors of the hierarchy, even when mathematics and the humanities were included. These results support a “gradualist” view of scientific knowledge, suggesting that the Hierarchy of the Sciences provides the best rational framework to understand disciplines' diversity. A deeper grasp of the relationship between subject matter's complexity and consensus could have profound implications for how we interpret, publish, popularize and administer scientific research.

Suggested Citation

  • Daniele Fanelli & Wolfgang Glänzel, 2013. "Bibliometric Evidence for a Hierarchy of the Sciences," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
  • Handle: RePEc:plo:pone00:0066938
    DOI: 10.1371/journal.pone.0066938
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    1. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    2. Vincent Larivière & Éric Archambault & Yves Gingras & Étienne Vignola‐Gagné, 2006. "The place of serials in referencing practices: Comparing natural sciences and engineering with social sciences and humanities," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(8), pages 997-1004, June.
    3. Daniele Fanelli, 2013. "Redefine misconduct as distorted reporting," Nature, Nature, vol. 494(7436), pages 149-149, February.
    4. Bertuglia, Cristoforo Sergio & Vaio, Franco, 2005. "Nonlinearity, Chaos, and Complexity: The Dynamics of Natural and Social Systems," OUP Catalogue, Oxford University Press, number 9780198567912.
    5. Leydesdorff, Loet & Rafols, Ismael, 2011. "Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations," Journal of Informetrics, Elsevier, vol. 5(1), pages 87-100.
    6. Cranmer, Skyler J. & Desmarais, Bruce A., 2011. "Inferential Network Analysis with Exponential Random Graph Models," Political Analysis, Cambridge University Press, vol. 19(1), pages 66-86, January.
    7. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    8. Attila V. Varga, 2011. "Measuring the semantic integrity of scientific fields: a method and a study of sociology, economics and biophysics," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 163-177, July.
    9. Paul F. Skilton, 2006. "A comparative study of communal practice: Assessing the effects of taken-for-granted-ness on citation practice in scientific communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 73-96, July.
    10. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    11. Moshe Yitzhaki, 2002. "Relation of the title length of a journal article to the length of the article," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 435-447, July.
    12. Nicolaisen, Jeppe & Frandsen, Tove Faber, 2012. "Consensus formation in science modeled by aggregated bibliographic coupling," Journal of Informetrics, Elsevier, vol. 6(2), pages 276-284.
    13. Daniele Fanelli, 2012. "Negative results are disappearing from most disciplines and countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 891-904, March.
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    Cited by:

    1. Wolfgang Glänzel & Koenraad Debackere, 2022. "Various aspects of interdisciplinarity in research and how to quantify and measure those," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5551-5569, September.
    2. John G. Benjafield, 2020. "Vocabulary sharing among subjects belonging to the hierarchy of sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1965-1982, December.
    3. Pei-Shan Chi & Wolfgang Glänzel, 2022. "An article-based cross-disciplinary study of reference literature for indicator improvement," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7077-7089, December.
    4. Julián D. Cortés, 2022. "Identifying the dissension in management and business research in Latin America and the Caribbean via co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7111-7125, December.
    5. Harrison, Richard T., 2023. "W(h)ither entrepreneurship? Discipline, legitimacy and super-wicked problems on the road to nowhere," Journal of Business Venturing Insights, Elsevier, vol. 19(C).
    6. Mario Coccia, 2020. "The evolution of scientific disciplines in applied sciences: dynamics and empirical properties of experimental physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 451-487, July.
    7. Muñoz-Écija, Teresa & Vargas-Quesada, Benjamín & Chinchilla Rodríguez, Zaida, 2019. "Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study," Journal of Informetrics, Elsevier, vol. 13(4).
    8. Seolmin Yang & So Young Kim, 2023. "Knowledge-integrated research is more disruptive when supported by homogeneous funding sources: a case of US federally funded research in biomedical and life sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3257-3282, June.
    9. Mario Coccia, 2021. "Evolution and structure of research fields driven by crises and environmental threats: the COVID-19 research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9405-9429, December.

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