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Lin Zhang, Fan Qi, Gunnar Sivertsen, Liming Liang, David Campbell; Gender differences in the patterns and consequences of changing research directions in scientific careers. Quantitative Science Studies 2024; doi: https://doi.org/10.1162/qss_a_00330
Abstract
Changes of research directions in scientific careers are related to the so-called “essential tension” between exploration of new knowledge and exploitation of established knowledge in research and innovation. Changes of research directions are thereby assumed to influence the evolution of science in general. Research has shown that such changes may also affect the success of individual scientists in their careers. However, the gender dimension of this aspect of career development is so far understudied. There is also need for more dynamic indicators to record and interpret career developments in macro data. This study combines the gender perspective with the introduction of new indicators. We selected more than 29,000 scientists in Physics & Astronomy and studied them over six decades using a bibliographic dataset from Scopus. We find that women are less likely to change research directions than their men counterparts, and that the research performance of women is less negatively affected by changing research directions. We discuss the policy implications of these findings as well as the methodological advancement related to the new indicators of career development.
Excerpt citing Namsor API
The authors’ gender is inferred using a machine-learning-based classifier, Namsor. It estimates the possibilities of a binary classification of gender based on the authors’ names and countries. We evaluate the results by the gender inference score derived from name and country information, as well as name-only inference scores. To ensure the reliability of gender inference, we included only those scientists whose scores (name and country based or name-only based) exceed a threshold of 0.85. Asian scientists are excluded due to the unsatisfactory performance of the gender inference algorithm in their case. Ultimately, we obtained 26,568 scientists with masculine-coded names and 2,626 with feminine-coded names using reliable gender inference, accounting for 74.22% of all the scientists meeting the criteria above.
Caption by DALL-E : illustration based on the title “Gender differences in the patterns and consequences of changing research directions in scientific careers.” It captures the concept of gender differences, challenges, and opportunities in scientific careers with a symbolic crossroads theme.
About NamSor
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.