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Does the use of open, non-anonymous peer review in scholarly publishing introduce bias? Evidence from the F1000Research post-publication open peer review publishing model
Allen, Liz Papas, Eleanor-Rose Nyakoojo, Zena Weigert, Verena Thelwall, Michael
Allen, Liz
Papas, Eleanor-Rose
Nyakoojo, Zena
Weigert, Verena
Thelwall, Michael
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2020-07-05
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Abstract
As part of moves towards open knowledge practices, making peer review open is cited as a way to enable fuller scrutiny and transparency of assessments around research. There are now many flavours of open peer review in use across scholarly publishing, including where reviews are fully attributable and the reviewer is named. This study examines whether there is any evidence of bias in two areas of common critique of open, non-anonymous (named) peer review – and used in the post-publication, peer review system operated by the open-access scholarly publishing platform F1000Research. First, is there evidence of potential bias where a reviewer based in a specific country assesses the work of an author also based in the same country? Second, are reviewers influenced by being able to see the comments and know the origins of a previous reviewer? Based on over 4 years’ of open peer review data, we found some evidence, albeit weak, that being based in the same country as an author may influence a reviewer’s decision, while there was insufficient evidence to conclude that being able to read an existing published review prior to submitting their review encourages conformity. Thus, whilst immediate publishing of peer review reports appears to be unproblematic, caution may be needed when selecting same-country reviewers in open systems if other studies confirm these results.
Citation
Allen, L., Papas, E., Nyakoojo, Z., Weigert, V. and Thelwall, M (2020) Does the use of open, non-anonymous peer review in scholarly publishing introduce bias? Evidence from the F1000Research post-publication open peer review publishing model, Journal of Information Science, 47 (6), pp. 809-820. https://doi.org/10.1177/0165551520938678
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Journal article
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en
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This is an accepted manuscript of an article published by SAGE in Journal of Information Science on 05/07/2020. The published version can be accessed here: https://doi.org/10.1177/0165551520938678
The accepted version of the publication may differ from the final published version.
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0165-5515