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Fig. 3 | Applied Network Science

Fig. 3

From: Gender and collaboration patterns in a temporal scientific authorship network

Fig. 3

Women are disproportionately underrepresented among authors with many publications in INFORMS. There appears to be an additional underrepresentation of women among authors with many publications, beyond what would already be expected by the lower proportion of women authors in the data. To quantify this effect, we modeled the degree distributions of each gender as a power law, using the exponent γ as a measure of how “heavy” the tail of these distributions are. By considering the number of authors with k publications as an independent Poisson variable with mean n(k)=ckγ, we maximized the likelihood of the data over the space of c and γ. The results showed a steeper power law for women (γwomen≈2.73 vs. γmen≈2.14 in 1993 and γwomen≈2.37 vs. γmen≈2.09 in 2016). To quantify the significance of this difference, we repeatedly randomized the gender labels of the nodes and considered the distributions of the fitted exponents γ as the null distribution for the observed result. We found that the z-scores of the observed power-law exponents were about −9.4 for men and +11.6 for women in 1993, and about −6.9 for men and +10.5 for women in 2016, all highly significant. This indicates that women are disproportionately underrepresented among authors with many publications in INFORMS. However, this difference seems to be attenuating, as suggested by the decrease in the difference between γwomen and γmen during this time

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