IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v84y2010i2d10.1007_s11192-009-0107-x.html
   My bibliography  Save this article

How accurately does Thomas Kuhn’s model of paradigm change describe the transition from the static view of the universe to the big bang theory in cosmology?

Author

Listed:
  • Werner Marx

    (Max Planck Institute for Solid State Research)

  • Lutz Bornmann

    (Professorship for Social Psychology and Research on Higher Education)

Abstract

Up to the 1960s the prevalent view of science was that it was a step-by-step undertaking in slow, piecemeal progression towards truth. Thomas Kuhn argued against this view and claimed that science always follows this pattern: after a phase of “normal” science, a scientific “revolution” occurs. Taking as a case study the transition from the static view of the universe to the Big Bang theory in cosmology, we appraised Kuhn’s theoretical approach by conducting a historical reconstruction and a citation analysis. As the results show, the transition in cosmology can be linked to many different persons, publications, and points in time. The findings indicate that there was not one (short term) scientific revolution in cosmology but instead a paradigm shift that progressed as a slow, piecemeal process.

Suggested Citation

  • Werner Marx & Lutz Bornmann, 2010. "How accurately does Thomas Kuhn’s model of paradigm change describe the transition from the static view of the universe to the big bang theory in cosmology?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 441-464, August.
    • Handle: RePEc:spr:scient:v:84:y:2010:i:2:d:10.1007_s11192-009-0107-x
    DOI: 10.1007/s11192-009-0107-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-009-0107-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-009-0107-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Chaomei & Chen, Yue & Horowitz, Mark & Hou, Haiyan & Liu, Zeyuan & Pellegrino, Donald, 2009. "Towards an explanatory and computational theory of scientific discovery," Journal of Informetrics, Elsevier, vol. 3(3), pages 191-209.
    2. Helmut A. Abt, 2000. "Do Important Papers Produce High Citation Counts?," Scientometrics, Springer;Akadémiai Kiadó, vol. 48(1), pages 65-70, June.
    3. Steven A. Morris, 2005. "Manifestation of emerging specialties in journal literature: A growth model of papers, references, exemplars, bibliographic coupling, cocitation, and clustering coefficient distribution," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(12), pages 1250-1273, October.
    4. Werner Marx & Manuel Cardona, 2009. "The citation impact outside references — formal versus informal citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 1-21, July.
    5. Lucio-Arias, Diana & Leydesdorff, Loet, 2009. "The dynamics of exchanges and references among scientific texts, and the autopoiesis of discursive knowledge," Journal of Informetrics, Elsevier, vol. 3(3), pages 261-271.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pablo Contreras Kallens & Rick Dale, 2018. "Exploratory mapping of theoretical landscapes through word use in abstracts," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1641-1674, September.
    2. Xuan Zhen Liu & Hui Fang, 2012. "Peer review and over-competitive research funding fostering mainstream opinion to monopoly. Part II," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 607-616, February.
    3. Matthieu Ballandonne & Igor Cersosimo, 2021. "A note on reference publication year spectroscopy with incomplete information," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4927-4939, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meyer, Eric T. & Schroeder, Ralph, 2009. "Untangling the web of e-Research: Towards a sociology of online knowledge," Journal of Informetrics, Elsevier, vol. 3(3), pages 246-260.
    2. Tian Wang & Zhaoping Yang & Xiaodong Chen & Fang Han, 2022. "Bibliometric Analysis and Literature Review of Tourism Destination Resilience Research," IJERPH, MDPI, vol. 19(9), pages 1-16, May.
    3. Xian Li & Ronald Rousseau & Liming Liang & Fangjie Xi & Yushuang Lü & Yifan Yuan & Xiaojun Hu, 2022. "Is low interdisciplinarity of references an unexpected characteristic of Nobel Prize winning research?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2105-2122, April.
    4. Burmaoglu, Serhat & Sartenaer, Olivier & Porter, Alan, 2019. "Conceptual definition of technology emergence: A long journey from philosophy of science to science policy," Technology in Society, Elsevier, vol. 59(C).
    5. Kim, Hyoungshick & Yoon, Ji Won & Crowcroft, Jon, 2012. "Network analysis of temporal trends in scholarly research productivity," Journal of Informetrics, Elsevier, vol. 6(1), pages 97-110.
    6. Hamid Darvish & Yaşar Tonta, 2016. "Diffusion of nanotechnology knowledge in Turkey and its network structure," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 569-592, May.
    7. Huang, Cui & Yang, Chao & Su, Jun, 2021. "Identifying core policy instruments based on structural holes: A case study of China’s nuclear energy policy," Journal of Informetrics, Elsevier, vol. 15(2).
    8. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    9. Jake R. Nelson & Tony H. Grubesic, 2018. "Environmental Justice: A Panoptic Overview Using Scientometrics," Sustainability, MDPI, vol. 10(4), pages 1-18, March.
    10. Srayan Datta & Eytan Adar, 2018. "A generative model for scientific concept hierarchies," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-19, February.
    11. Krzysztof Klincewicz, 2016. "The emergent dynamics of a technological research topic: the case of graphene," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 319-345, January.
    12. Andrej Kastrin & Dimitar Hristovski, 2021. "Scientometric analysis and knowledge mapping of literature-based discovery (1986–2020)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1415-1451, February.
    13. Zhao Zhai & Ming Shan & Amos Darko & Albert P. C. Chan, 2021. "Corruption in Construction Projects: Bibliometric Analysis of Global Research," Sustainability, MDPI, vol. 13(8), pages 1-21, April.
    14. Reindert K. Buter & Ed. C. M. Noyons & Anthony F. J. Raan, 2011. "Searching for converging research using field to field citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 325-338, February.
    15. Yiming Xiao & Han Wu & Guohua Wang & Hong Mei, 2021. "Mapping the Worldwide Trends on Energy Poverty Research: A Bibliometric Analysis (1999–2019)," IJERPH, MDPI, vol. 18(4), pages 1-22, February.
    16. Yuqing Fang, 2015. "Visualizing the structure and the evolving of digital medicine: a scientometrics review," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 5-21, October.
    17. Martin Meyer & Kevin Grant & Piera Morlacchi & Dagmara Weckowska, 2014. "Triple Helix indicators as an emergent area of enquiry: a bibliometric perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 151-174, April.
    18. Fritze, Martin P. & Urmetzer, Florian & Khan, Gohar F. & Sarstedt, Marko & Neely, Andy & Schäfers, Tobias, 2018. "From Goods to Services Consumption: A Social Network Analysis on Sharing Economy and Servitization Research," SMR - Journal of Service Management Research, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 2(3), pages 3-16.
    19. Gaston Heimeriks & Ron Boschma, 2014. "The path- and place-dependent nature of scientific knowledge production in biotech 1986–2008," Journal of Economic Geography, Oxford University Press, vol. 14(2), pages 339-364.
    20. Saikou Y. Diallo & Christopher J. Lynch & Ross Gore & Jose J. Padilla, 2016. "Identifying key papers within a journal via network centrality measures," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1005-1020, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:84:y:2010:i:2:d:10.1007_s11192-009-0107-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.