Opinion ID: 771988
Heading Depth: 3
Heading Rank: 2

Heading: Comparison to an Average Male

Text: 23 Marist next argues that plaintiff should not be permitted to establish a prima facie case by comparing herself to a statistical composite of male faculty members. Marist relies again primarily on a case from the Fourth Circuit: [t]he plaintiff may not compare herself to a hypothetical male with a composite average of a group's skill, effort, and responsibility. Houck v. Va. Polytechnic Inst. & State Univ., 10 F.3d 204, 206 (4th Cir. 1993); see also Pollis v. New Sch. for Soc. Research, 913 F. Supp. 771, 784 (S.D.N.Y. 1996) ([I]t is doubtful whether statistics tending to demonstrate a difference between the average salaries paid to male and female employees can satisfy plaintiff's prima facie burden.), rev'd in part on other grounds, 132 F.3d 115 (2d Cir. 1997). In language not quoted by Marist, however, the Houck court stated that the plaintiff must identify a particular male for the inquiry. Houck, 10 F.3d at 206. Houck stands for the proposition that plaintiff may not substitute a statistical male comparator for an actual one. Plaintiff here has identified an actual male comparator. Furthermore, after its decision in Houck, the Fourth Circuit has implied that once a male comparator has been identified, statistical averages may be employed. See Strag, 55 F.3d at 950. In fact, that court, in both Strag and Houck, has indicated that such evidence may be required because isolated incidents of discrimination may not be sufficient to make out a prima facie case. See Strag, 55 F.3d at 950; Houck, 10 F.3d at 206-07. 24 We hold that statistical evidence of a gender-based salary disparity among comparable professors properly contributed to plaintiff's case in conjunction with her identification of a specific male comparator. Because plaintiff was the only Assistant Professor of equivalent seniority in the Criminal Justice department, and one of only three in her division, experts for both sides extrapolated from the pool of the entire faculty at Marist to establish a sufficiently large statistical sample size. We think this was permissible not only to establish liability, but also in calculating damages. 25 The problem with comparing plaintiff's pay only to that of a single male employee is that it may create the impression of an Equal Pay Act violation where no widespread gender discrimination exists. Moreover, in the calculation of damages, such a comparison may either grant the plaintiff a windfall where the male comparator is paid particularly well, or improperly limit her recovery where the male comparator, though better compensated than she, is paid less than the typical man of substantially equal skill, effort, and responsibility. On similar reasoning, the Ninth Circuit Court of Appeals has noted that where multiple comparators exist, the plaintiff is not permitted simply to select the best-compensated male to establish her case. Rather, 26 the proper test for establishing a prima facie case in a professional setting such as that of a college is whether the plaintiff is receiving lower wages than the average of wages paid to all employees of the opposite sex performing substantially equal work and similarly situated with respect to any other factors, such as seniority, that affect the wage scale. 27 Hein, 718 F.2d at 916; see also Pollis, 913 F. Supp. at 785 (Once [plaintiff] has introduced evidence tending to show that certain male professors are 'equal' to her . . ., I will allow her to average their salaries, and compare this figure to her own salary.); id. at n.8 (I am . . . reluctant to allow plaintiff to identify one equally situated professor, and use that professor's salary to compute her damages. Such an approach would allow [plaintiff] to artificially inflate damages by selecting the highest paid, equally situated professor.). 28 To be sure, this case differs from Hein because here plaintiff has identified only one male comparator. Thus, neither expert averaged the salaries of male comparators who actually existed. Instead, they found it necessary to use the entire Marist faculty to establish a sufficiently large sample size, extrapolating from professors who did not compare to plaintiff across all five variables to predict what a male professor who would have so compared typically would have been paid. Cf. Pollis, 132 F.3d at 121 (citing several cases holding that discrimination may not be proven by statistics based on an insufficient sample size). Their conclusions were remarkably consistent. Dr. Parides arrived at a figure of $50,640, as compared to Dr. Ashenfelter's figure of $50,696. Based on the regression analysis she performed before conducting content analysis, Dr. Poris detected a similar disparity. Plaintiff's male comparator, Dr. White, earned $46,168. Therefore, in this case, the pay disparity, and thus plaintiff's damages, were increased when her salary was compared to the statistical composite instead of to the male comparator's actual salary. 29 It is undisputed that multiple regression analysis, which was used by the experts here, is a scientifically valid statistical technique for identifying discrimination. See Ottaviani, 875 F.2d at 367 (Using multiple regression analysis, individual plaintiffs can make predictions about what job or job benefits similarly situated employees should ideally receive, and then can measure the difference between the predicted treatment and the actual treatment of those employees.). We hold that, under the circumstances of this case, regression analysis, based on a larger pool of male employees and that controlled for differences within each variable as between the plaintiff and members of the male pool, properly supported plaintiff's case and was appropriately employed to calculate damages. In so holding, we note that, because plaintiff both identified a male comparator and provided statistical evidence of gender-based discrimination, we need not decide whether either type of evidence standing alone would have been sufficient to prove discrimination under the Equal Pay Act.