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. 2020 Mar 3;117(9):4609-4616.
doi: 10.1073/pnas.1914221117. Epub 2020 Feb 18.

Historical comparison of gender inequality in scientific careers across countries and disciplines

Junming Huang  1   2   3 , Alexander J Gates  1 , Roberta Sinatra  4   5 , Albert-László Barabási  6   7   8   9
Affiliations

Historical comparison of gender inequality in scientific careers across countries and disciplines

Junming Huang et al. Proc Natl Acad Sci U S A..

Abstract

There is extensive, yet fragmented, evidence of gender differences in academia suggesting that women are underrepresented in most scientific disciplines and publish fewer articles throughout a career, and their work acquires fewer citations. Here, we offer a comprehensive picture of longitudinal gender differences in performance through a bibliometric analysis of academic publishing careers by reconstructing the complete publication history of over 1.5 million gender-identified authors whose publishing career ended between 1955 and 2010, covering 83 countries and 13 disciplines. We find that, paradoxically, the increase of participation of women in science over the past 60 years was accompanied by an increase of gender differences in both productivity and impact. Most surprisingly, though, we uncover two gender invariants, finding that men and women publish at a comparable annual rate and have equivalent career-wise impact for the same size body of work. Finally, we demonstrate that differences in publishing career lengths and dropout rates explain a large portion of the reported career-wise differences in productivity and impact, although productivity differences still remain. This comprehensive picture of gender inequality in academia can help rephrase the conversation around the sustainability of women's careers in academia, with important consequences for institutions and policy makers.

Keywords: STEM; gender inequality; science of science; scientific careers.

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Conflict of interest statement

Competing interest statement: A.-L.B. is founder of Nomix, Foodome, and Scipher Medicine, companies that explore the role of networks in health. All other authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
Gender imbalance since 1955. (A) The number of active female (orange) and male (blue) authors over time and the total proportions of authors (Inset). (B and C) The proportion of female authors in several disciplines (B) and countries (C); for the full list, see SI Appendix, Tables S3 and S4. (D) The academic publishing career of a scientist is characterized by his or her temporal publication record. For each publication, we identify the date (gold dot) and number of citations after 10 years c10 (gold line, lower). The aggregation by year provides the yearly productivity (light gold bars), while the aggregation over the entire career yields the total productivity (solid yellow bar, right) and total impact (solid yellow bar, right). Career length is calculated as the time between the first and last publication, and the annual productivity (dashed gold line) represents the average yearly productivity. Authors drop out from our data when they published their last article.
Fig. 2.
Fig. 2.
Gender gap in scientific publishing careers. The gender gap is quantified by the relative difference between the mean for male (blue) and female (orange) authors. In all cases the, relative gender differences are statistically significant, as established by the two-sided t test, with P values < 10−4, unless otherwise stated (see SI Appendix, section S4.A for test statistics). (A–E) Total productivity broken down by percentile (A), discipline (B), country (C), affiliation rank (D), and decade (E). The gender gap in productivity has been increasing from the 1950s to the 2000s. (F–J) Total impact subdivided by percentile (F), discipline (G), country (H), affiliation rank (I), and decade (J). (K–O) Annual productivity is nearly identical for male and female authors when subdivided by percentile (K), discipline (L), country (M), affiliation rank (N), and decade (O). (P–T) Career length broken down by percentile (P), discipline (Q), country (R), affiliation rank (S), and decade (T).
Fig. 3.
Fig. 3.
Controlling for career length. (A and B) The gender gap in career length strongly correlates with the gender gap in productivity across disciplines (Pearson correlation, 0.80) (A) and countries (Pearson correlation, 0.56) (B). A gender gap of 0.0% indicates gender equality, while negative gaps indicate the career length or productivity is greater for male careers, and positive gaps indicate the feature is greater for female careers. (C) In a matching experiment, equal samples are constructed by matching every female author with a male author having an identical discipline, country, and career length. (D) The average productivity provided by the matching experiment for career length compared to the population; the gender gap is reduced from 27.4% in the population to 7.8% in the matched samples. (E) The average impact provided by the matching experiment for career length compared to the original unmatched sample. Where visible, error bars denote 1 SD.
Fig. 4.
Fig. 4.
Author’s age-dependent dropout rate. (A) Dropout rate for male (blue) and female (orange) authors over their academic ages. (B) The cumulative survival rate for male and female authors over their academic ages. (C and D) The effect of controlling for the age-dependent dropout rate on the gender gaps in total productivity (C) and impact (D). (E) The total impact gap is eliminated in the matched sample based on total productivity. (F) The gender gap in the total number of collaborators is eliminated in the matched sample based on total productivity.
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