A mathematical approach to the effects of gender bias and cross gender interactions on careers in STEM.

Creating a mathematical model to predict participation in STEM fields would allow communities such as the APS understand better how to influence participation in physics. We propose a model that simulates the progression of women in male-dominated fields starting from the equations for a model predator-prey type system. We include interactions between the dominant and non-dominant populations and investigate how they effect the percent of the non-dominant population. We believe that such a model effectively capters some of the dynamics erported by researchers directly collecting data about the experiences of women in these fields.