Since 2018, NamSor has been used append gender to authors in RePEC (Research Papers in Economics). Overall, 25.8% of economists are female.
New research used NamSor Gender API to allocate likely gender to authors in The Lancet Global Health scientific journal. Findings
What if you could build your a search engine with an inverted gender bias ? We’ve connected Algolia and NamSor API to search IMDB top 5000 movies.
With our open source connector, any PowerBI table that has personal names can be enriched with gender information or other diversity analytics (country of origin / ethnicity …)
French researchers have used patronyms to explore diversity amongst different population groups and professions. In France, where ethnic statistics are not collected, this new approach provides interesting insights about French society.
Abstract— The low share of women in computer science is documented by many surveys. Most of these studies are based on registrations or enrolments of universities or other scientific institutions. In this paper, we present a new approach to a) analyse the gender gap in the group of scientists that are currently active in research and b) classify differences for different fields of computer science. This group comprises professors, industrial researchers, senior lecturers, postdoctoral researchers, and doctoral students shortly before finishing their theses. The proportion of women in a specific scientific area of computer science might provide valuable information for strategies to recruit women as postdocs or professors.
Science-Metrix develops bibliometric indicators to measure women’s contribution to Science, based on NamSor Gender API.
Using a library or an APIs to infer the gender from a given name, is a common way to fix
A new research by Elsevier used NamSor Gender API along with other methods, to provide an analysis of research performance through