Speaker
Huey-Wen Lin
Description
In this work, we take all the papers since 2000 that are classified as primary hep-lat to study whether there is any race or gender bias in the journal-publication process. We implement machine learning to predict the race and gender of authors based on their names, and look for measurable differences between publication outcomes based on author category.
We would like to invite discussion on how journals can make improvements in the near future and how institutions or grant offices should account for these publication differences in gender and race.
