The Third Circuit reverses and remands summary judgment, in a (surprisingly) unpublished opinion, for a putative class of female Amtrak employees who complained that “requiring all union employees to have one year of service in their current position before they could be considered for promotion has a disparate impact” in violation of Title VII.
Stagi v. National Railroad Passenger Corporation, No. 09-3512 (3d Cir. Aug. 16, 2010): The claim is summarized –
“Plaintiffs Stagi and Ladd are long-time Amtrak employees who have been employed in both its union and management ranks during their careers. Stagi began her career at Amtrak in 1973 as a reservation and information clerk, and eventually worked her way up to various union positions until the early 1990s, when she was promoted to a management position. She was in a management position in April 2002 when she was laid off as a result of a corporate-wide management restructuring effort. Ladd was promoted to management in 1986 and continued to be promoted through management until April 2002, when her job was similarly eliminated. Because they had previously worked in Amtrak’s union ranks, they were both entitled to ‘bump down’ into a union position based on their retrained union seniority. In the year following their layoffs, both applied for management vacancies, some of which they had previously held or supervised. They were both blocked by the one-year rule from being considered for those positions. Stagi remains in her union position. Ladd was not able to return to management before 2004, when she left on long-term disability and retired with benefits inferior to those she would have enjoyed had she been permitted to access a management position.”
On summary judgment, both sides produced expert reports on the issue of whether there was a meaningful statistical disparity between men and women in promotions. Plaintiffs submitted an expert report by Mark R. Killingsworth, while Amtrak submitted a responsive expert report by David W. Griffin. A key dispute between the parties was whether the plaintiff expert appropriately composed “proxy” pools of workers available for promotion.
The district court concluded that the Killingsworth report was unpersuasive in raising a prima facie inference of disparate impact, and granted summary judgment. “This decision was based on two main considerations: (1) that ‘the applicant pool plaintiffs analyzed to demonstrate the disparate impact of Amtrak’s policy erroneously compares employees who may not have the minimal qualifications for the particular jobs at issue,’ and (2) that ‘when viewed in context, plaintiffs’ evidence of discrimination lacks practical significance.'” In sum:
“The District Court objected . . . to Dr. Killingsworth’s decision to ‘aggregate’ all of the individual Feeder Pools into ‘one giant pool’ (the ‘Aggregated Pool’) in order to analyze ‘the degree to which the Policy disqualified women in the Aggregated Pool relative to men.’ Id. Specifically, Dr. Killingsworth combined all 716 individual Feeder Pools into one large pool in order to conduct his statistical analysis. The District Court noted that when Dr. Killingsworth analyzed the data using a ‘corrected probit analysis’ (which corrects for the fact that the same individual might appear in more than one pool), the results yielded a standard deviation of 3.855, with a p-value of less than 0.001-results which the District Court acknowledged were ‘unlikely to have
occurred as a result of chance alone.'”
The panel holds, by contrast, that Killingsworth’s method is neither compelled nor precluded by accepted statistical practice:
“[T]he only issue is whether the District Court was correct in finding that Dr. Killingsworth’s statistical analysis was, in effect, legally irrelevant to satisfying Plaintiffs’ burden with respect to their prima facie case because his analysis used aggregation, and in particular the Aggregated Pool, in conducting his statistical analysis. We find that Dr. Killingsworth’s decision to aggregate the data, although not obviously correct, is also not obviously incorrect, and so there remains a genuine issue of material fact-whether the one-year rule caused a disparate impact on Amtrak’s female employees.
The panel reviews the three statistical standards cited in discrimination cases, and finds two wanting: the 80% rule (which the panel states “has come under substantial criticism, and has not been particularly persuasive, at least as a prerequisite for making out a prima facie disparate impact case”) and so-called “practical significance” (derived from the EEOC Uniform Guidelines, which note that “[s]maller differences in selection rate may nevertheless constitute adverse impact, where they are significant in both statistical and practical terms,” 29 C.F.R. § 1607.4(D)). The panel expressly disaffirms any requirement of practical significance (“we decline to require such a showing as part of a plaintiff’s prima facie case”). It also rejects any added requirement “that the statistical disparity be ‘substantial.'”
Relying instead on the standard of statistical significance (the conventional test, measured by 2 to 3 standard deviations), the panel finds that there was a triable issue about the prima facie case.
The panel also notes that aggregation may improve the reliability of the analysis: “Additionally, there may be good reasons to aggregate data in a case such as this-reasons that have nothing to do with simply picking and choosing the model which will generate the most favorable results for plaintiffs’ case. Perhaps most significantly, as the Fourth Circuit has observed, ‘by increasing the absolute numbers in the data, chance will more readily be excluded as a cause of any disparities found.’ Lilly v. Harris-Teeter Supermarket, 720 F.2d 326, 336 n.17 (4th Cir. 1983). This makes intuitive sense. ‘For example, if a coin were tossed ten times . . . and came up heads four times, no one would think the coin was biased (0.632 standard deviations), but if this same ratio occurred for a total of 10,000 tosses, of which 4,000 were heads, the result could not be attributed to chance (20 standard deviations).” Id. Here, by combining all of those candidacies in the 716 Feeder Pools into one Aggregated Pool, Dr. Killingsworth was better able to test whether the difference in the ineligibility rate for men and women was merely the product of chance. Many courts have found such a reason for aggregating compelling.”