14 | Developments in Equal Pay Litigation ©2023 Seyfarth Shaw LLP be a piece of circumstantial proof bolstering an inference of discrimination, but to be useful, the statistics must clearly show actual differences in treatment, and their usefulness therefore ‘depends on all of the surrounding facts and circumstances.’”96 The court then compared plaintiff’s salary with those of her male comparators and found that she had been paid more than two male comparators in her first year in their pay grade, and that other differences in pay were explained by other non-discriminatory factors of the employer’s compensation system.97 Proving Wage Disparities in Class and Collective Actions. In class and collective actions, the identification of a wage disparity is even more complex. The use of statistics to show disparities in pay across employee groups is often critical in such cases. For example, in Spencer v. Virginia State University,98 the Fourth Circuit affirmed a decision that rejected an attempt by a tenured Associate Professor in the Department of Sociology to use statistics to establish that she was paid less than termappointed Associate Professors in other departments.99 The court noted the unique features of academia that present special challenges for the EPA claimant: “[p]rofessors are not interchangeable like widgets. Various considerations influence the hiring, promotion, and compensation of different professorial jobs.”100 The Fourth Circuit noted that, in the academic context, “work is an exercise in intellectual creativity that can be judged only according to intricate, field-specific, and often subjective criteria.”101 Accordingly, an EPA plaintiff must provide the court with more than broad generalities to establish a claim.102 The Fourth Circuit held that plaintiff’s expert had failed to identify a general disparity between the pay of men and women at the university: “[h]is efforts revealed no statistically significant disparity within each ‘school.’ If anything, this evidence undermines [plaintiff’s] claimed inference of discrimination.”103 In Bridewell-Sledge v. Blue Cross of California,104 a California state court based its denial of class certification on a close analysis of the parties’ competing expert reports.105 The court held that plaintiffs’ expert had failed to apply the proper criteria for assessing the potential wage differential under the California Fair Pay Act because the law only prohibits such wage disparities for employees doing “substantially similar work” when viewed as a composite of skill, effort, and responsibility, and performed 96 Id. at *26 (quoting Int'l Bhd. of Teamsters v. U.S., 431 U.S. 324, 340 (1977)). 97 Id. 98 Spencer v. Va. State Univ., 919 F.3d 199 (4th Cir. 2019). 99 The district court had held, among other things, that the plaintiff had failed to establish that those positions were the same, noting that: “the functional responsibilities that comprised ‘teaching a class’ and the skillset required in doing so varied across all three departments.” Spencer v. Va. State Univ., No. 3:16-cv-989-HEH, 2018 WL 627558, at *9 (E.D. Va. Jan. 30, 2018). But the court also held that the analysis performed by plaintiff’s own expert showed that the university did not suffer from any systemic gender-related wage disparity. Id. at *10. Among other things, plaintiff’s expert found that plaintiff’s comparators were overpaid in comparison to their peers, including both male and female faculty members, and that there was not a statistically significant level of male faculty being paid more than their female counterparts by school. Id. The district court concluded that the “absence of systemic discrimination combined with improper identification of a male comparator suggests a failure to establish a prima facie case.” Id. (quoting Stag v. Bd. of Trs., Craven Cmty. Coll., 55 F.3d 943, 950 (4th Cir. 1995)). 100 Spencer v. Va. State Univ., 919 F.3d 199, 204 (4th Cir. 2019). 101 Id. at 205. 102 Id. 103 Id. at 206. 104 Bridewell-Sledge v. Blue Cross of Cal., No. BC477451, 2018 Cal. Super. LEXIS 3879 (Cal. Super. Ct. Aug. 28, 2018). Plaintiffs’ expert performed a regression analysis that sought to take account of race, sex, years of company services, age, and educational attainment to conclude that males were paid more relative to females in a manner that was both large in absolute magnitude of the pay differential, and statistically significant. 105 Id. at *39. California courts may consider statistical evidence as “indicators of a defendant’s centralized practices in order to evaluate whether common behavior towards similarly situated plaintiffs makes class certification appropriate.” Id. at *26 (quoting Sav-On Drug Stores, Inc. v. Super. Ct., 34 Cal. 4th 319, 333 (Cal. 2004)). Even though there is no requirement under the California Fair Pay Act or the federal EPA for plaintiffs to prove intentional discrimination or discriminatory animus, courts often allow the use of evidence—including expert statistical evidence—that would tend to demonstrate intentional discrimination. See also Storrs v. Univ. of Cincinnati, No. 1:15-cv-136, 2018 WL 684759, at *3 (S.D. Ohio Feb. 2, 2018) (“[Plaintiff] may present facts and argument regarding sex discrimination to the extent these facts (1) prove the elements of her EPA claim, (2) demonstrate that [employer] acted willfully, and (3) rebut [employer’s] affirmative defense that the discrepancy was based on a factor ‘other than sex.’ Although intentional discrimination is not an element of an EPA claim, courts typically allow evidence that demonstrates that the defendant acted willfully or suggests that the defendant’s affirmative defense is pretextual.”) (emphasis omitted) (citing Boaz v. Fed. Express Corp., 107 F. Supp. 3d 861, 891 (W.D. Tenn. 2015) (“Although intent to discriminate is not a requisite element for making out an EPA claim, a showing of discriminatory motivation may be used to demonstrate that an affirmative defense on which the employer relies is in fact pretextual.”) (quotation omitted); Simpson v. Merchs. & Planters Bank, 441 F.3d 572, 580 (8th Cir. 2006)).
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