Algorithmic Gender Inference

In collaboration with Lincoln Mullen and Bridget Baird, I helped develop a computational method to infer the gender of names by using historical data. This approach offers a higher degree of nuance by incorporating the changing nature of naming practices over time - “Leslie,” for instance, went from being a predominantly male name in the early twentieth century to a predominantly female name by the end of the century. Gender package for R builds on an earlier prototype written in Python. I’ve applied this method to study the persistent gender gap in the American Historical Review. (Blevins & Mullen, 2015)