Scientific eminence and scientific hierarchy: bibliometric prediction of fellowship in the Australian Academy of Science

Nick Haslam () and Naomi Baes
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Nick Haslam: The University of Melbourne
Naomi Baes: The University of Melbourne

Scientometrics, 2023, vol. 128, issue 12, No 18, 6659-6674

Abstract: Abstract Research metrics are known to predict many markers of scientific eminence, but fellowship in learned academies has not been examined in this context. The present research used Scopus-based citation indices, including a composite index developed by Ioannidis et al., (PLoS Biol 14:e1002501, 2016, https://doi.org/10.1371/journal.pbio.1002501 ) that improves cross-field comparison, to predict fellowship in the Australian Academy of Sciences (AAS). Based on ideas of a hierarchy of the sciences, the study also examined whether researchers from natural science fields were advantaged in achieving AAS fellowship relative to researchers from fields toward the social science end of the hierarchy. In a comprehensive sample of top global researchers, the composite index and its components all strongly differentiated Australian researchers who were elected as AAS fellows from those who were not. As predicted, when composite index scores were statistically controlled, researchers in physical and mathematical sciences were more likely to achieve fellow status than biological scientists, who were much more likely to achieve it than psychological, cognitive, and social scientists. Researchers in basic science fields also had an election advantage over those in more applied and technological fields. These findings suggest that recognition by learned academies may be predicted by citation indices, but may also be influenced by the perceived hardness, prestige, and purity of research fields.

Keywords: Bibliometrics; Citation analysis; Hierarchy of science; Learned academy (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11192-023-04870-8

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