ArticleFrontiers in research metrics and analytics2023
Are female scientists underrepresented in self-retractions for honest error?
Article in Frontiers in research metrics and analytics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Retractions are among the effective measures to strengthen the self-correction of science and the quality of the literature. When it comes to self-retractions for honest errors, exposing one's own failures is not a trivial matter for researchers. However, self-correcting data, results and/or conclusions has increasingly been perceived as a good research practice, although rewarding such practice challenges traditional models of research assessment. In this context, it is timely to investigate who have self-retracted for honest error in terms of country, field, and gender. We show results on these three factors, focusing on gender, as data are scarce on the representation of female scientists in efforts to set the research record straight. We collected 3,822 retraction records, including research articles, review papers, meta-analyses, and letters under the category "error" from the Retraction Watch Database for the 2010-2021 period. We screened the dataset collected for research articles (2,906) and then excluded retractions by publishers, editors, or third parties, and those mentioning any investigation issues. We analyzed the content of each retraction manually to include only those indicating that they were requested by authors and attributed solely to unintended mistakes. We categorized the records according to country, field, and gender, after selecting research articles with a sole corresponding author. Gender was predicted using
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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.