The gender gap in science: How long until women are equally represented?

By L. Holman, Devi M Stuart-Fox, Cindy E. Hauser. PLoS Biology, 2018

653 citations recorded by the source corpus.

Women comprise a minority of the Science, Technology, Engineering, Mathematics, and Medicine (STEMM) workforce. Quantifying the gender gap may identify fields that will not reach parity without intervention, reveal underappreciated biases, and inform benchmarks for gender balance among conference speakers, editors, and hiring committees. Using the PubMed and arXiv databases, we estimated the gender of 36 million authors from >100 countries publishing in >6000 journals, covering most STEMM disciplines over the last 15 years, and made a web app allowing easy access to the data (https://lukeholman.github.io/genderGap/). Despite recent progress, the gender gap appears likely to persist for generations, particularly in surgery, computer science, physics, and maths. The gap is especially large in authorship positions associated with seniority, and prestigious journals have fewer women authors. Additionally, we estimate that men are invited by journals to submit papers at approximately double the rate of women. Wealthy countries, notably Japan, Germany, and Switzerland, had fewer women authors than poorer ones. We conclude that the STEMM gender gap will not close without further reforms in education, mentoring, and academic publishing.

Subfields: Gender Studies, Public Health, Environmental and Occupational Health, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5638f55b0f9a444f39c0ce7b4dee4b65885ea095

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Gender Studies

1. Dan Jurafsky
2. Lucía Santamaría
3. Helena Mihaljević

In Public Health, Environmental and Occupational Health

1. Albert-László Barabási
2. Lucía Santamaría
3. Helena Mihaljević

In Statistics and Probability

1. Daniel A. McFarland
2. Albert-László Barabási
3. Dan Jurafsky
4. Lucía Santamaría
5. Helena Mihaljević

Citations in the corpus

• Comparison and benchmark of name-to-gender inference services (2018, methodology): “…case is particularly relevant e.g. for437 researchers in scientometrics looking for the most suitable gender inference algorithm for a particular438 data source such as PubMed, whereas the former is most appropriate when analyzing different data439 collections, as e.g. in Holman et al. (2018).”
• Historical comparison of gender inequality in scientific careers across countries and disciplines (2019, background): “Paradoxically, the gradual increase in the fraction of women in science (5) (Fig.”
• The Diversity–Innovation Paradox in Science (2019, background): “41 – 43 ) and race We then measure the fraction of students in a discipline-year carrying the same gender or race, e.g., the percentage of women in education in 1987 when a student is a woman, the percentage of underrepresented minority scholars when a student is an underrepresented minority, and…”