The high scholarly value of grey literature before and during Covid-19
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AbstractNew academic knowledge in journal articles is partly built on peer reviewed research already published in journals or books. Academics can also draw from non-academic sources, such as the websites of organisations that publish credible information. This article investigates trends in the academic citing of this type of grey literature for 17 health, media, statistics, and large international organisations, with a focus on Covid-19. The results show substantial and steadily increasing numbers of citations to all 17 sites, with larger increases from 2019 to 2020. In 2020, Covid-19 citations to these websites were particularly common for news organisations, the WHO, and the UK Office for National Statistics, apparently for up-to-date information in the rapidly changing circumstances of the pandemic. Except for the UN, the most cited URLs of each organisation were not traditional report-like grey literature but were other types, such as news stories, data, statistics, and general guidance. The Covid-19 citations to most of these websites originated primarily from medical research, commonly for coronavirus data and statistics. Other fields extensively cited some of the non-health websites, as illustrated by social science (including psychology) studies often citing UNESCO. The results confirm that grey literature from major websites has become even more important within academia during the pandemic, providing up-to-date information from credible sources despite a lack of academic peer review. Researchers, reviewers, and editors should accept that it is reasonable to cite this information, when relevant, and evaluators should value academic work that supports these non-academic outputs.
CitationKousha, K., Thelwall, M. & Bickley, M. (2022) The high scholarly value of grey literature before and during Covid-19, Scientometrics, 127, pp. 3489–3504. https://doi.org/10.1007/s11192-022-04398-3
DescriptionThis is an accepted manuscript of an article published by Springer Nature in Scientometrics on 21/05/2022, available online: https://doi.org/10.1007/s11192-022-04398-3 The accepted version of the publication may differ from the final published version.