PoS - Proceedings of Science
Volume 396 - The 38th International Symposium on Lattice Field Theory (LATTICE2021) - Poster
Is there any gender/race bias in hep-lat primary publication? Machine-Learning Evaluation of Author Ethnicity and Gender
H.W. Lin
Full text: pdf
Pre-published on: May 16, 2022
Published on:
In this work, we analyze papers 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 classification.
We would like to invite discussion on how journals can make improvements in their editorial process and how institutions or grant offices should account for these publication differences in gender and race.
DOI: https://doi.org/10.22323/1.396.0052
How to cite

Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in "proceeding" format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.