2019 Pay Equity Study Results: Social Sciences

Ladder Rank Salary Data

The salary data for all Ladder Rank Faculty in the School of Social Sciences are plotted below.
As a function of rank, step, and gender:

As a function of rank, step, and ethnicity:

Multiple Linear Regression Analysis

Multiple regression analysis of salary vs rank/step. As indicated in Table 1, simplest model with only demographic variables shows that relative to white male faculty, women earn salaries that are 17% lower, Asian faculty 9.3% and URM faculty 14% lower. Only 11% of salary variation is explained by this model. After all control factors are added, 92% of salary variation is explained by a model with demographic, experience, field, and rank variables. After adjusting for covariates, relative to white male faculty, salaries are 0.7% lower for faculty who are women, 2.7% higher for Asian, and 3.9% higher for URM faculty. This model also shows demographic variables are not statistically significant.

Progression Analysis

The progression data for all Social Sciences Ladder Rank Faculty, are plotted below.  Normative progression is defined in the Progression Matrix.

Progress by gender:

Progress by ethnicity:

Progress Rate Analysis

Using a simple t-test, results indicate that there is no statistically significant difference in progression rate means by either gender or ethnicity when compared to white male faculty. Normative progression is defined in the Progression Matrix.

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