Research metrics can be a useful way to show the impact of your work and the attention that it receives. Although metrics have limitations in how they are calculated and have best practices that should be followed (see the Leiden Manifesto, the Declaration on Research Assessment, and the Metric Tide for more information), it’s important to understand the biases that also exist in article citation patterns. Not only do women and people of color receive less recognition for their work, but having a lower article citation rate can also affect their careers. For example, citation metrics are sometimes used as part of the decision-making process for awarding grants and often play a role for faculty promotion and tenure.
Citational justice (also referred to as citational ethics or inclusive citations) is to take action to reduce these inequities in citation patterns. One such action would be for authors to make an effort to cite authors outside of who they know. There are also tools that can analyze the reference lists of papers and database search results to probabilistically assign gender and race of the first and last authors. By knowing the gender and race proportions in your reference list, you might consider going back to the literature to see if there are any relevant papers from underrepresented groups that were overlooked in your initial searches.