The discussion below contains excerpts from the book Human Capital Systems, Analytics and Data Mining.
In Data Analytics a Dependency Network uses statistical analysis and data to create graphs of relationships between group nodes and their corresponding dependencies. In the dependency network view shown below, the strongest links are shown by connectors from attribute categories to predictor attributes.
This dependency network image above shows that the highest US Government GS grade levels have the strongest relationships to the male gender category, while the lowest GS grades have the strongest connection to the female gender category.
This above confirms earlier findings of gender-based occupation upward
mobility problems for women as discussed in the book Human Capital Systems, Analytics and Data Mining.
It further dilutes the findings of other research in regard to significant average gender-based pay differences.
When female versus male federal service salaries are compared, women are paid equal to men when comparing jobs of equal value. Poor mobility of women into the higher occupational pay ranks distorts female-to-male pay differences as a whole, due to the skewed nature of the employment profile of women to men.
This also underscores the fact that gender pay equity when measured by average salaries is generally distorted by politicians and the popular press.