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Abstract

Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self-citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014-20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2-0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.

Date

22. 6.2023 18:11:50

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Abstract

If communication in research and development is efficient, then the current cognitive situation in any specialty should fully reflect all available relevant information. Available evidence suggests that communication in R&D is not in that sense efficient, and a priori arguments seem to show that it could not be. But we try to show that the evidence and arguments are inconclusive, and that the question of effiency is an open one. It is also one which information science has an interest in pursuing

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Abstract

Relevant information known to be available may go unused in research and development because of information overload or because its use is excluded by deliberate policy. Exclusion by policy shows that R&D is not, and does not aim at always being, efficient in the sense of fully reflecting all available relevant information. It may still be efficient relatice to chosen strategies of information use and non-use. Overload may be a sign of strategic error, or may be accepted as routine and normal