**By Dana Britton and Cynthia Daniels**, Faculty Co-directors of the Rutgers AAUP-AFT Salary Equity Program

As implemented, the Faculty Salary Equity Program involves two steps. The first is the choice of comparators to whom the applicant believes their salary should be equivalent. The first determination is made by the Dean, who either declines the application or forwards comments and an approved set of comparators to the applicant and to University Compensation Services (UCS). Assuming the Dean chooses comparators, **the Dean has affirmed that the applicant and the comparators are basically equivalent in academic merit.**

### What Is the UCS Regression and What Does It Do?

Step two is the recommendation of a salary adjustment amount by UCS. For many applicants, this will involve a regression analysis performed by UCS (and actually developed on UCS’s behalf by a paid consultant for the law firm Jackson Lewis) that predicts salaries based on an analysis of the university’s entire salary database at a given point in time.

The philosophy behind using regression is not inherently problematic. One way to think of regression analysis is that it is an “adjuster.” For example, one of the regression variables is rank. Most faculty would agree that full professors in a given department should have higher salaries than associate professors. Since that is generally true at the university, the regression’s coefficient will lower the size of the salary gap for an associate professor applicant whose approved comparator is a full professor.

Let’s say the initial gap between an associate professor applicant and their approved full professor comparator is $50,000. This will be indicated in the UCS letter as the “Requestor/Comparator Pay Gap” (as a negative number: –$50,000).

The regression predicts a salary for full professors in that department that is $25,000 higher than associate professors. This becomes the “Explainable Pay Gap” in the UCS letter (in this case, negative, as in –$25,000). This means that $25,000 of the gap between the applicant and their comparator is due to the fact that the latter is a full professor. We are using one comparator for the sake of simplicity –if there is more than one, the University averages comparator salaries.

UCS then subtracts that explainable number from the initial gap and the “unexplainable gap.” This is the size of the award if there is any gap remaining. In our example, it is $25,000 (again indicated by UCS as a negative number). The formula in this case is: (–$50,000) – (–$25,000) = (–$25,000). The applicant is awarded $25,000, including back pay retroactive to the date of the application.

This is an oversimplified example. There are four variables in the equation used by UCS: rank, position title (usually, but not always the same as rank), pay plan (which varies little among applicants) and “discipline” (more on this below). If applicants and their comparators do not differ on these four factors, the regression analysis does not apply and the “explainable gap” will be zero.

When they do differ, the regression will be applied to adjust these differences up or down using coefficients derived from the existing University salary database. This presents at least two serious problems.

- Any existing inequalities in salary are replicated; they are “baked into” the salary recommendation made by UCS. We might agree, as in the example above, that full professors should make, on average, $25,000 more than associates and hence that the university salary database reflects an equitable difference. We might not agree, however, that faculty in Engineering should make, on average, $100,000 more than those in English. But because this difference already exists in the salary database on which it is based, the regression will simply replicate it.
- The regression does not adjust for “discipline”; it adjusts for a combination of department and campus. Discipline codes include a campus designation, as in “FASC – English,” “SAS –English,” and “SASN-English.” Again, because the salary database reflects differences between English departments on these three campuses, the regression replicates these differences. Applying the coefficients used in the first round of applications, these are the predicted AY salaries for assistant professors in English: Camden = $86,020, Newark = $97,951, and New Brunswick = $108,464.

Hence what the regression is saying is that the salary of an assistant professor in English at Camden *should be* $22,444 lower than an assistant professor of English at New Brunswick. This will be the “explainable” gap (assuming the applicants are the same on all the other regression variables). Indeed, the most common scenario in which the regression lowers salaries occurs in comparisons between Camden faculty and those at Newark and New Brunswick. Camden faculty are “discounted” relative to their peers on other campuses. This is less common at Newark, but there are some disciplines in which this also occurs, as in the example above.

In this example, the Camden assistant professor would have to show a salary gap with their New Brunswick comparator of more than $22,444 before they received any award at all. This is the case EVEN THOUGH the Dean has indicated that the two applicants are comparable in academic merit.

### How Do I Challenge This?

According to the settlement signed on December 6, 2022:

Faculty members appealing Chancellor decisions may challenge the application of regression equations to the particular faculty member but not the use of regression analysis. Faculty members also may challenge other methodologies used by Compensation Services, the Dean, or the Chancellor to calculate the pay equity adjustment.

We understand this to mean that applicants cannot challenge their salary recommendation by simply saying something along the lines of “regression is illegitimate and should be discarded in my case.” Here is our advice:

- If your UCS letter has an “explainable” difference with a negative sign (–$25,000), and you want to challenge this, contact us at equityprogram@rutgersaaup.org, and we will help you sort out how the regression applied in your case.
- One possible strategy would be to challenge the explainable difference (the discount) itself. You could argue, for example, that the Dean has already judged you equivalent to your comparator at New Brunswick. Given that, it’s unfair that the university thinks you should be paid $22,000 less for producing equally meritorious work.
- Another possible strategy—though not an uncontroversial one—would be to argue that you are different from your departmental colleagues and hence do not deserve the same “discount.” If you take this line, you would need to show that there is something unique about you that means you deserve a higher salary than the regression generates. Hence you aren’t really challenging the discount itself (in fact, you are agnostic about it), but you believe it does not apply to you.

You may use elements of either of these strategies if they apply. Because the appeal/review committees have not met, we have no way of knowing what might be most persuasive.

### Is There Anything We Can Do about This in the Long Term?

Yes. The union is working to remove the regression from the process of salary determination and is particularly critical of its replication of intercampus salary differences. Get involved in our contract campaign. You can sign up for Strike School workshops and look for information and updates about our campaign at the Contract Resource Center.