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Record W6924971079 · doi:10.17605/osf.io/jshg7

Reviewer selection biases editorial decisions on manuscripts

2017· other· en· W6924971079 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2017
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSelection (genetic algorithm)Reliability (semiconductor)MEDLINEPeer reviewEditorial boardLetter to the editorAssociate editor

Abstract

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Many journals, including the Journal of Neurochemistry, enable authors to list peer reviewers as “preferred” or “opposed” suggestions to the editor. At the Journal of Neurochemistry, the handling editor (HE) may follow recommendations or select non-author-suggested reviewers (non-ASRs). We investigated whether selection of author-suggested reviewers (ASRs) influenced decisions on a paper, and whether differences might be related to a reviewers’, editor’s or manuscript’s geographical location. In this retrospective analysis, we compared original research articles submitted to the Journal of Neurochemistry from 2013 through 2016, that were either reviewed exclusively by non-ASRs, by at least one ASR, by at least one reviewer marked by the author as “opposed”, or none. Manuscript outcome, reviewer rating of manuscript quality, rating of the reviewers’ performance by the editor (R-score), time to review, and the country of the editor, reviewers and manuscript author were analyzed using non-parametric rank-based comparisons, chi-square (x2) analysis, multivariate linear regression, one-way analysis of variance, and inter-rater reliability determination. Original research articles that had been reviewed by at least one ASR stood a higher chance of being accepted (525/1006 = 52%) than papers that had been reviewed by non-ASRs only (579/1800 = 32%). An article was 2.4 times more likely to be accepted than rejected by an ASR compared to a non-ASR (Pearson’s x2(1) = 181.3, p<0.05). At decision, the editor did not simply follow the reviewers’ recommendation but had a balancing role: Rates of recommendation from reviewers for rejection were 11.2% (139/1241) with ASRs vs. 29.0% (1379/4755) with non-ASRs (this is a ratio of 0.39 where 1 means no difference between rejection rates for both groups), whereas the proportion of final decisions to reject was 24.7% (248/1006) vs. 45.7% (822/1800) (a ratio of 0.54, considerably closer to 1). Recommendations by non-ASRs were more favorable for manuscripts from USA/Canada and Europe than for Asia/Pacific or Other countries. ASRs judged North American manuscripts most favorably, and judged papers generally more positively (mean: 2.54 on a 1-5 scale) than did non-ASRs (mean: 3.16) reviewers, whereas time for review (13.28 vs. 13.20 days) did not differ significantly between these groups. We also found that editors preferably assigned reviewers from their own geographical region, but there was no tendency for reviewers to judge papers from their own region more favorably. Our findings strongly confirm a bias towards lower rejection rates when ASRs assess a paper, which led to the decision to abandon the option to recommend reviewers at the Journal of Neurochemistry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.056

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.144
GPT teacher head0.329
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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