Observational studyBMJ open2020
Gender and ethnic differences in publication of BMJ letters to the editor: an observational study using machine learning.
Observational study in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- China and the U.S. produce more impactful AI research when collaborating together.Scientific reports · 2024Article
- Ethnicity and gender trends of UK authors inEClinicalMedicine · 2023Article
- The Under-representation and Stagnation of Female, Black, and Hispanic Authorship in the Journal of the American Medical Association and the New England Journal of Medicine.Journal of racial and ethnic health disparities · 2023Article
- Non-White scientists appear on fewer editorial boards, spend more time under review, and receive fewer citations.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Does writing style affect gender differences in the research performance of articles?: An empirical study of BERT-based textual sentiment analysis.Scientometrics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo analyse the relationship between first author's gender and ethnicity (estimated from first name and surname), and chance of publication of rapid responses in the
designA retrospective observational study.
settingWebsite of the BMJ (BMJ.com).
participantsPublicly available rapid responses submitted to BMJ.com between 1998 and 2018.
main outcome measuresPublication of a rapid response as a letter to the editor in the BMJ.
resultsWe analysed 113 265 rapid responses, of which 8415 were published as letters to the editor (7.4%). Statistically significant univariate correlations were found between odds of publication and first author estimated gender and ethnicity, multiple authors, declaration of conflicts of interest, the presence of Twitter handle, word count, reading ease, spelling and grammatical mistakes, and the presence of references. Multivariate analysis showed that first author estimated gender and ethnicity predicted publication after taking into account the other factors. Compared to white authors, black authors were 26% less likely to be published (OR: 0.74, CI: 0.57-0.96), Asian and Pacific Islander authors were 46% less likely to be published (OR: 0.54, CI: 0.49-0.59) and Hispanic authors were 49% less likely to be published (OR: 0.51, CI: 0.41-0.64). Female authors were 10% less likely to be published (OR: 0.90, CI: 0.85-0.96) than male authors.
conclusionEthnic and gender differences in rapid response publication remained after accounting for a broad range of features, themselves all predictive of publication. This suggests that the reasons for the differences of these groups lies elsewhere.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.