Online from: 1977
Subject Area: Library and Information Studies
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|Title:||Interpretations and misinterpretations of scientometric data in the report of the Royal Society about the scientific landscape in 2011|
|Author(s):||Péter Jacsó, (University of Hawaii at Manoa, Honolulu, Hawaii, USA)|
|Citation:||Péter Jacsó, (2011) "Interpretations and misinterpretations of scientometric data in the report of the Royal Society about the scientific landscape in 2011", Online Information Review, Vol. 35 Iss: 4, pp.669 - 682|
|Keywords:||China, Databases, Measurement, Publications, Reports, Research, Sciences, Search output, United Kingdom|
|DOI:||10.1108/14684521111161990 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – This paper aims to discuss some caveats about the findings of Part 1 of the Royal Society's report from the perspective of the choice and reliability of the source base, and the bibliometric and scientometric indicators.
Design/methodology/approach – The paper argues that the Royal Society's report gives too much emphasis to the growth rate of the publications of Chinese researchers when interpolating those data and forecasting that, within the decade and possibly as early as 2013, China will be ahead of even the USA in terms of the number of publications.
Findings – In an era when the “publish or perish” slogan is replaced by the “get cited or perish” mantra, the report barely discusses how much China is behind the world average and especially the above countries in terms of the most important scientometric indicators that take into account the productivity/quantity aspect and the citedness of publications as a proxy for quality.
Originality/value – The paper illustrates that there are much better measures for the assessment of research activity than the one-dimensional productivity numbers, such as the h-index or the uncitedness rate, and the citations/publication rate where China is far below and the USA is far above the world average scores, and uses some charts to paint a more realistic picture of the scientific landscape.
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