Do women undertake interdisciplinary research more than men, and do self-citations bias observed differences? A paper published in Quantitative Science Studies (2022), authored by Henrique Pinheiro, Matt Durning, David Campbell.
Some studies have shown that women undertake interdisciplinary research more than men, whereas other studies have shown no difference by gender. Women have also been shown to self-cite less often than men, a difference at least partly mediated through differences in career stages and prior productivity. Existing evidence on gender-based differences in interdisciplinarity may therefore be biased. If interdisciplinarity is inferred from the disciplinary diversity of a paper’s cited references, a greater share of self-citations by men could decrease their measured interdisciplinarity relative to women. Such biases could lead to erroneous conclusions, because after correcting for self-citations one might uncover that women participate in interdisciplinary research equally to, or less than, men. Given that funding for interdisciplinary research is gaining in importance, obtaining accurate measurements of interdisciplinarity by gender is highly relevant for funders so that they can take appropriate action(s) in leveling the playing field across gender. For instance, evidence suggests women are sometimes advised not to participate in interdisciplinary research due to the risk it represents for their career progression. This study shows that a paper’s interdisciplinarity increases with the presence of female authors, accounting or not for self-citations in the interdisciplinarity measurement.
gender, interdisciplinarity, measurement bias, self-citation, women’s participation in science
We’re proud to announce that 2022 has seen the number of scientific articles using or citing NamSor nearly double.
Also, we’re happy to launch our new blog in Spanish language,
- El uso de la autocita como medidor de disparidad en la investigación interdisciplinar entre hombres y mujeres
- ¿Qué tan “neutrales” pueden ser las IA al disminuir el sesgo racial y de género?
- ¿Las mujeres matemáticas son menos citadas que los hombres?
NamSor™ Applied Onomastics is a European vendor of sociolinguistics software (NamSor sorts names). NamSor mission is to help understand international flows of money, ideas and people. We proudly support Gender Gap Grader.