In this letter to the editor we discuss the crucial role of algorithmic approaches in gender assignment and their impact on publication and citation patterns within the scientific workforce. We conducted an analysis of Scientometrics articles and found a series of weaknesses and bias of current gender assignment algorithms. While some studies presented clear and replicable approaches, others lacked transparency, hindering the reproducibility of results. We highlight the importance of transparent reporting. We argue that transparent, robust, and replicable reporting is essential to address limitations and promote more inclusive practices in the field of bibliometrics. By providing clear methodologies, researchers can enhance the quality and reliability of their studies, ultimately advancing the understanding of gender disparities in science.

Paper accepted for publication in Scientometrics.