Please wait...
About This Project
Women are grievously underrepresented in the mathematical sciences. Because publication of research is key to academic career advancement and because research has repeatedly uncovered gender bias penalizing women in professional circumstances, we use tools of data science to study 600 mathematical sciences journal editorial boards. We quantify gender representation on these boards and examine its association with characteristics such as impact factor, publishing house, and mathematical subfield.
More Lab Notes From This Project
Browse Other Projects on Experiment
Related Projects
AI analysis of soil pH with a smartphone camera
This project aims to democratize access to soil analysis by developing a machine-learning model to predict...
Can low-cost and readily available water quality testers accurately map pollution levels in Indian rivers?
Lack of reliable water quality data is leading to serious global health issues. The UNEP estimates that...
Microplastic Monitoring Network in Islands and Coastal Zone
The coast of Santa Catarina represents 7% of the Brazilian coast and contains 6 areas relevant to conservation...