Gender differences in research areas and topics: An analysis of publications in 285 fields

TL;DR

This study analyzes gender differences in research interests, topics, and methods across 285 fields in US academia, revealing nuanced patterns beyond traditional gender stereotypes and suggesting broader strategies to address gender disparities.

Contribution

It provides a detailed comparison of male and female researchers' publication topics and methods across many fields, highlighting factors beyond the people/thing dimension influencing gender representation.

Findings

Females show greater interest in veterinary science and cell biology.

Males are more interested in abstraction, politics, and law.

Females tend to use exploratory and qualitative methods, males more quantitative.

Abstract

Although the gender gap in academia has narrowed, females are underrepresented within some fields in the USA. Prior research suggests that the imbalances between science, technology, engineering and mathematics fields may be partly due to greater male interest in things and greater female interest in people, or to off-putting masculine cultures in some disciplines. To seek more detailed insights across all subjects, this article compares practising US male and female researchers between and within 285 narrow Scopus fields inside 26 broad fields from their first-authored articles published in 2017. The comparison is based on publishing fields and the words used in article titles, abstracts, and keywords. The results cannot be fully explained by the people/thing dimensions. Exceptions include greater female interest in veterinary science and cell biology and greater male interest in abstraction, patients, and power/control fields, such as politics and law. These may be due to other factors, such as the ability of a career to provide status or social impact or the availability of alternative careers. As a possible side effect of the partial people/thing relationship, females are more likely to use exploratory and qualitative methods and males are more likely to use quantitative methods. The results suggest that the necessary steps of eliminating explicit and implicit gender bias in academia are insufficient and might be complemented by measures to make fields more attractive to minority genders.