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Structure of the scientific research and science policy

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  • Peter Vinkler

    (Hungarian Academy of Sciences)

Abstract

Several scientometric indicators of 29 countries were analysed according to main scientific fields (Life, Natural, Applied, and Agricultural Sciences). The difference of the individual countries from the world average in the number of journal papers devoted to the main scientific fields was related to the GDP/capita index of the countries. Four types of research structure could be distinguished by a cluster analysis: countries preferring Life Sciences with higher or lower share in Natural Sciences, and countries preferring Natural Sciences with higher or lower share in Life Sciences. From the results it concludes, the development of a country (measured as GDP/capita) strongly influences but, it does not determine the structure of science by research fields in the country. The number of journal papers in a country classified as top cited (i.e. they belong to the 1% of papers most frequently cited in WoS ESI) was related to the total number of papers published by the country. The so obtained Top paper rate index (TPR) may represent the contribution of countries to the advance of science. Analysis of the TPR indicator of a country by research fields (i.e. Chemistry, Clinical Medicine, Space Science, etc.) may indicate strengths and weaknesses of the research on national level. Relating the Relative field citedness indicator (RW) of a country to the corresponding TPR value, conclusions may be drawn as to the homogeneity of impact of research within a country by fields.

Suggested Citation

  • Peter Vinkler, 2018. "Structure of the scientific research and science policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 737-756, February.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:2:d:10.1007_s11192-017-2568-7
    DOI: 10.1007/s11192-017-2568-7
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    References listed on IDEAS

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    2. Valderrama-Zurian, J.C. & Melero-Fuentes, D. & Aleixandre-Benavent, R., 2019. "Origin, characteristics, predominance and conceptual networks of eponyms in the bibliometric literature," Journal of Informetrics, Elsevier, vol. 13(1), pages 434-448.
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    4. Mingyang Wang & Jiaqi Zhang & Shijia Jiao & Xiangrong Zhang & Na Zhu & Guangsheng Chen, 2020. "Important citation identification by exploiting the syntactic and contextual information of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2109-2129, December.
    5. Jielan Ding & Per Ahlgren & Liying Yang & Ting Yue, 2018. "Disciplinary structures in Nature, Science and PNAS: journal and country levels," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1817-1852, September.
    6. Henry Laverde-Rojas & Juan C. Correa, 2019. "Can scientific productivity impact the economic complexity of countries?," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 267-282, July.

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