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Analysis of the division of labor in China’s high-quality life sciences research

Author

Listed:
  • Xiaoyu Cai

    (National Science Library, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Tao Han

    (National Science Library, Chinese Academy of Sciences)

Abstract

International cooperation has always been a popular subject in academic research. Recently, with the rise of “Author Contributions,” quantitative research using the authors' division of labor in scientific research has provided a new perspective for the measure of international cooperation. In this article, international collaboration is analyzed in a more fine-grained way, namely by considering the importance of contributions of different authors at the national level. Semantic structures of the division of labor are extracted via text mining from the author contribution sections of life sciences publications in the Nature Index’s 68 journals, are categorized with two predefined rule libraries into corresponding division categories. Then, quantitative analysis of the Chinese division of labor is conducted from the perspectives of both quantity and structure and at both the national and international levels. From the perspective of quantity, at both the national and international levels, Chinese contributions in any category of the division of labor have been increasing in the past 10 years, not only in proportion, but also in as ranked among other countries, especially in the category of experiment operation. From the structural perspective, China’s contributions have become more structurally balanced in the past decade. In 2017, China's structure of the division of labor was between those of BRICS countries and G7 countries. From the co-authorship perspective, the significant differences between China and other countries are reflected in both sample and data collection and tools and technology.

Suggested Citation

  • Xiaoyu Cai & Tao Han, 2020. "Analysis of the division of labor in China’s high-quality life sciences research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1077-1094, November.
    • Handle: RePEc:spr:scient:v:125:y:2020:i:2:d:10.1007_s11192-020-03582-7
    DOI: 10.1007/s11192-020-03582-7
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    References listed on IDEAS

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