ArticleFrontiers in big data2019
Reflections on Gender Analyses of Bibliographic Corpora.
Article in Frontiers in big data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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Who cites it
8 citing papers in PubMed.
- Women climate scientists are connected, productive, and successful but have shorter careers.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Inequality in measuring scholarly success: Variation in the h-index within and between disciplines.PloS one · 2025Article
- Inferring gender from first names: Comparing the accuracy of Genderize, Gender API, and the gender R package on authors of diverse nationality.PLOS digital health · 2024Article
- The effect of the COVID-19 pandemic on the gender gap in research productivity within academia.eLife · 2023Article
- A critical analysis of plant science literature reveals ongoing inequities.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Important Questions Deserve Rigorous Analysis: A Cautionary Note About Selection Bias.Journal of the American Heart Association · 2022Article
- A machine learning approach to quantify gender bias in collaboration practices of mathematicians.Frontiers in big data · 2022Article
- Diversifying history: A large-scale analysis of changes in researcher demographics and scholarly agendas.PloS one · 2022Article
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
The interplay between an academic's gender and their scholarly output is a riveting topic at the intersection of scientometrics, data science, gender studies, and sociology. Its effects can be studied to analyze the role of gender in research productivity, tenure and promotion standards, collaboration and networks, or scientific impact, among others. The typical methodology in this field of research is based on a number of assumptions that are customarily not discussed in detail in the relevant literature, but undoubtedly merit a critical examination. Presumably the most confronting aspect is the categorization of gender. An author's gender is typically inferred from their name, further reduced to a binary feature by an algorithmic procedure. This and subsequent data processing steps introduce biases whose effects are hard to estimate. In this report we describe said problems and discuss the reception and interplay of this line of research within the field. We also outline the effect of obstacles, such as non-availability of data and code for transparent communication. Building on our research on gender effects on scientific publications, we challenge the prevailing methodology in the field and offer a critical reflection on some of its flaws and pitfalls. Our observations are meant to open up the discussion around the need and feasibility of more elaborated approaches to tackle gender in conjunction with analyses of bibliographic sources.
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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.