Evidence map›Paper›PMID 39652394›Full record

ArticleJournal of medical Internet research2024

Use of ChatGPT to Explore Gender and Geographic Disparities in Scientific Peer Review.

Paul Sebo

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Paul SeboUniversity of Geneva, Geneva, Switzerland.ORCID 0000-0001-7616-0017

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the realm of scientific research, peer review serves as a cornerstone for ensuring the quality and integrity of scholarly papers. Recent trends in promoting transparency and accountability has led some journals to publish peer-review reports alongside papers.

objectiveChatGPT-4 (OpenAI) was used to quantitatively assess sentiment and politeness in peer-review reports from high-impact medical journals. The objective was to explore gender and geographical disparities to enhance inclusivity within the peer-review process.

methodsAll 9 general medical journals with an impact factor >2 that publish peer-review reports were identified. A total of 12 research papers per journal were randomly selected, all published in 2023. The names of the first and last authors along with the first author's country of affiliation were collected, and the gender of both the first and last authors was determined. For each review, ChatGPT-4 was asked to evaluate the "sentiment score," ranging from -100 (negative) to 0 (neutral) to +100 (positive), and the "politeness score," ranging from -100 (rude) to 0 (neutral) to +100 (polite). The measurements were repeated 5 times and the minimum and maximum values were removed. The mean sentiment and politeness scores for each review were computed and then summarized using the median and interquartile range. Statistical analyses included Wilcoxon rank-sum tests, Kruskal-Wallis rank tests, and negative binomial regressions.

resultsAnalysis of 291 peer-review reports corresponding to 108 papers unveiled notable regional disparities. Papers from the Middle East, Latin America, or Africa exhibited lower sentiment and politeness scores compared to those from North America, Europe, or Pacific and Asia (sentiment scores: 27 vs 60 and 62 respectively; politeness scores: 43.5 vs 67 and 65 respectively, adjusted P=.02). No significant differences based on authors' gender were observed (all P>.05).

conclusionsNotable regional disparities were found, with papers from the Middle East, Latin America, and Africa demonstrating significantly lower scores, while no discernible differences were observed based on authors' gender. The absence of gender-based differences suggests that gender biases may not manifest as prominently as other forms of bias within the context of peer review. The study underscores the need for targeted interventions to address regional disparities in peer review and advocates for ongoing efforts to promote equity and inclusivity in scholarly communication.

Indexed as

Peer ReviewFemaleHumansJournal Impact FactorMalePeer Review, ResearchPeriodicals as TopicSex FactorsAfricaartificial intelligenceassessmentChatGPTcommunicationconsultationdiscriminationdisparitygendergender biasgeographicglobal southinequalitypeer reviewresearchersentiment analysiswoman

Identifiers

PMID39652394
PMCPMC11667125

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.