The academic status of reviewers predicts their language use
Zhuanlan Sun,
C. Clark Cao,
Chao Ma and
Yiwei Li
Journal of Informetrics, 2023, vol. 17, issue 4
Abstract:
Peer review plays an essential role in scientific research, but the influence of reviewers' academic status is often overlooked during this process. By accessing peer review reports, in this study we empirically investigate this effect. Specifically, we analyzed 2,580 peer review histories from eLife submissions between 2016 and 2021 to examine the relationship between reviewers’ academic status and their language usage in the first round of peer review. We focused on two types of language features: emotional features (e.g., positivity and subjectivity) and linguistic features (e.g., number of long words and complex words). Our findings revealed no significant reviewer bias of academic status, such that the reviewers’ comments with emotional features were not significantly associated with reviewers’ awareness of being more prestigious than the last corresponding author of the manuscripts. More accomplished reviewers, however, were more likely to use longer and more complex words. Additionally, the results of linguistic features remained robust in the group where the last author served as the last corresponding author. Overall, our findings suggest that the quality of peer review remains the primary consideration for reviewers when evaluating submissions. These results have significant implications for open peer review practices and the fair assessment of the peer review process.
Keywords: Peer review; Academic status; Language usage; Linguistic feature; Emotional feature (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157723000743
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:17:y:2023:i:4:s1751157723000743
DOI: 10.1016/j.joi.2023.101449
Access Statistics for this article
Journal of Informetrics is currently edited by Leo Egghe
More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().