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Medical theses and derivative articles: dissemination of contents and publication patterns

Author

Listed:
  • Mercedes Echeverria

    (Library of the Universidad Autonoma de Madrid)

  • David Stuart

    (King’s College London)

  • Tobias Blanke

    (King’s College London)

Abstract

Doctoral theses are an important source of publication in universities, although little research has been carried out on the publications resulting from theses, on so-called derivative articles. This study investigates how derivative articles can be identified through a text analysis based on the full-text of a set of medical theses and the full-text of articles, with which they shared authorship. The text similarity analysis methodology applied consisted in exploiting the full-text articles according to organization of scientific discourse IMRaD (Introduction, Methodology, Results and Discussion) using the TurnItIn plagiarism tool. The study found that the text similarity rate in the Discussion section can be used to discriminate derivative articles from non-derivative articles. Additional findings were: the first position of the thesis’s author dominated in 85 % of derivative articles, the participation of supervisors as coauthors occurred in 100 % of derivative articles, the authorship credit retained by the thesis’s author was 42 % in derivative articles, the number of coauthors by article was 5 in derivative articles versus 6.4 coauthors, as average, in non-derivative articles and the time differential regarding the year of thesis completion showed that 87.5 % of derivative articles were published before or in the same year of thesis completion.

Suggested Citation

  • Mercedes Echeverria & David Stuart & Tobias Blanke, 2015. "Medical theses and derivative articles: dissemination of contents and publication patterns," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 559-586, January.
    • Handle: RePEc:spr:scient:v:102:y:2015:i:1:d:10.1007_s11192-014-1442-0
    DOI: 10.1007/s11192-014-1442-0
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    References listed on IDEAS

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    1. Weeks, William B & Wallace, Amy E & Kimberly, B.C.Surott, 2004. "Changes in authorship patterns in prestigious US medical journals," Social Science & Medicine, Elsevier, vol. 59(9), pages 1949-1954, November.
    2. Zhaohui Sun & Mounir Errami & Tara Long & Chris Renard & Nishant Choradia & Harold Garner, 2010. "Systematic Characterizations of Text Similarity in Full Text Biomedical Publications," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-6, September.
    3. Rodrigo Costas & María Bordons, 2011. "Do age and professional rank influence the order of authorship in scientific publications? Some evidence from a micro-level perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 145-161, July.
    4. Nils T. Hagen, 2010. "Deconstructing doctoral dissertations: how many papers does it take to make a PhD?," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(2), pages 567-579, November.
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    Cited by:

    1. Bowen Ma & Chengzhi Zhang & Yuzhuo Wang & Sanhong Deng, 2022. "Enhancing identification of structure function of academic articles using contextual information," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 885-925, February.
    2. Paul Donner, 2022. "Algorithmic identification of Ph.D. thesis-related publications: a proof-of-concept study," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5863-5877, October.
    3. Inés M. Fernández-Guerrero & Zoraida Callejas & David Griol & Antonio Fernández-Cano, 2020. "Longitudinal patterns in Spanish doctoral theses on scientific medical information: a tertiary study," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1241-1260, August.
    4. Andrada Elena Urda-Cîmpean & Sorana D. Bolboacă & Andrei Achimaş-Cadariu & Tudor Cătălin Drugan, 2016. "Knowledge Production in Two Types of Medical PhD Routes—What’s to Gain?," Publications, MDPI, vol. 4(2), pages 1-16, June.

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