Track the genders in research to make sure countries are held accountable

Nature Index: A Data-Analysis of the Geographical Distribution of Women in Science, Technology and Engineering Topics from 2024 to 2024

The data set allows users to look at how disciplines perform in different countries. In the year 2024, authors based in the US, France and Canada had 34% of the total number of women. The United Kingdom comes in at 29% and India at 28%. Japan has among the lowest proportion of female authorship, at 16%. The United States and India are on an upward trajectory. The United States and India both increased over the course of the next ten years. The gap in South Korea narrowed by 2 points during the same period.

Providing data at the field or country level will allow for each community to know what’s happening inside their fields, as well as understand why trends are happening and how to do better.

The better the access to information that lays bare the inequities faced by women in pursuing careers in science, technology, engineering and mathematics, especially for positions of influence and leadership, the better equipped society will be to push back on unfair, antiquated systems and build a stronger research environment for all.

The United States, Canada and France had the highest percentage of female authors in the top ten countries.

The lowest-ranking topics — in which the gender gap is the widest — were mainly chemistry and physical sciences topics, many of which had less than 20% female co-authorship.

The Nature Index data-analysis team used a piece of artificial intelligence called the Chatbot to infer the author genders on the basis of their most likely country of origin and name in order to create the data set.

Some countries and territories have stronger name–gender associations — in other words, most people with a certain name will identify as a certain gender — than others, which can make the results of the analysis uneven. Most of the names in some countries such as Singapore and China have been removed from the analysis because they have low confidence that the model is accurate.