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Table 1.

Methods for gender distribution of employees in the CING section.

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Table 2.

Methods for collaborativeness in CING co-authorship network section.

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Fig 1.

Gender distribution of employees in the CING.

A. Histogram plots of the gender distribution of employees in the three divisions (Clinical Services, Research & Diagnostic and Support Services) in the CING. B. Histogram plots of the gender distribution of employees in the CING Departments (Clinics, Laboratories and Facilities). C. Histogram plots of the gender distribution of employees in the Clinical Services departments. D. Histogram plots of the gender distribution of employees in the Support Services departments of the CING.

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Fig 2.

Gender representation across positions in the CING.

A. Histogram plots of the gender distribution of employees in position rankings in the Research & Diagnostic division in the CING. B. Histogram plots of the two top ranks in the scientific strand. C. Histogram plots of the two top ranks in the clinical strand.

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Fig 3.

Comparison of years of service between males & females.

Histograms of recruited employees per 4-year interval.

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Fig 4.

Successive academic year postgraduate student gender representation.

Histogram of the percentage of female and male students recruited in across 8 consecutive academic years.

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Fig 5.

Gendered co-authorship network of CING employees.

Circle nodes indicate male authors, whereas square nodes indicate female authors. A link between two nodes/authors indicates co-authorship of at least one research paper.

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Fig 6.

Departmental co-authorship network of CING employees.

Square nodes indicate female authors and circle nodes indicate male authors. Node colour indicates department affiliation whereas a link between two nodes/authors indicates co-authorship of at least one research paper.

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Fig 7.

Raincloud plots for the male/female group centralities.

The raincloud plots with boxplots for the scores of the computed centralities for the female and male author groups in the CING co-authorship network including the average (1) degree for all (2) degree for male authors (M Degree) to male/female authors, (3) degree for female authors (F Degree) to male/female authors, (4) betweenness, (5) closeness and (6) eigenvector centrality.

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Fig 7 Expand

Table 3.

CING co-authorship network centralities.

The top quantile scored authors (N = 27) sorted based on the centralities degree (DEG), betweenness (BTW), closeness (CLS) and eigenvector (EIG). The authors’ gender (G) is included (F/M) as well as the annotation whether they are part of the Head (H) group with yes (Y) or no (N).

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Fig 8.

Post-hoc analysis for network centralities.

A-C. Post-hoc test (pairwise t-test and ANOVA) for the centralities Degree (DEG), Closeness (CLS) and Eigenvector (EIG), the groups whose means were statistically different from one another. The groups were (1) female heads (HF) to female non-heads (NHF), male heads (HM) and male non-heads (NHM). D. Post-hoc results for the betweenness (BTW) centrality which was tested with a non-parametric alternative method (pairwise Wilcoxon test and Kruskal-Wallis test). The significance of the p-value in each test in indicated with the following symbols: < 0.0001 ‘****’, < 0.001 ‘***’, < 0.01 ‘**’, < 0.05 ‘*’, < 1 ‘ns’.

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