Citation diversity statement
author/author
Recent work in several fields of science has identified a bias in citation practices such that papers from women and other minority scholars are undercited relative to the number of such papers in the field. Here, we sought to proactively evaluate whether references reflect the diversity of the field in thought, form of contribution, gender, race, ethnicity and other factors. First, we obtained the predicted gender of the first and last author of each reference by using databases that store the probability of a first name being carried by a woman. By this measure (and excluding self-citations to the first and last authors of our current paper), our references contain 8.89% woman(first)/woman(last), 13.33% man/woman, 14.17% woman/man and 63.6% man/man. This method is limited in that (i) names, pronouns and social media profiles used to construct the databases may not, in every case, be indicative of gender identity, and (ii) it cannot account for intersex, non-binary or transgender people. Second, we obtained the predicted racial/ethnic category of the first and last authors of each reference by databases that store the probability of a first and last name being carried by an author of color. By this measure (and excluding self-citations), our references contain 12.82% author of color (first)/author of color (last), 13.87% white author/author of color, 9.51% author of color/white author and 53.80% white author/white author. This method is limited in that (i) names and Florida Voter Data to make the predictions may not be indicative of racial/ethnic identity, and (ii) it cannot account for Indigenous and mixed-race authors or those who may face differential biases due to the ambiguous racialization or ethnicization of their names. We look forward to future work that could help us to better understand how to support equitable practices in science. This statement was created using cleanBib (