On Monday
April 2, 2018, the U.S. District Court, Southern District of New York, excluded
arbitrary expert testimony and accepted generalized proof of statistical
evidence to grant, in part, Plaintiffs’ class certification motion in
Chen-Oster, et al. v. Goldman Sachs, 2018 WL 1609267, at *1 (S.D.N.Y. Mar. 30,
2018).
The Class, consisting of
approximately 2,300 female current and former Associates and Vice Presidents in
the Investment Banking, Investment Management, and Securities Divisions of
Goldman Sachs, are challenging the company’s practices of paying women less,
giving them worse reviews, and passing them over for promotion. Specifically,
Plaintiffs allege that Goldman’s “360 review” performance evaluation process,
“forced ranking,” and “cross ruffing” (i.e., cross-checking procedure that
involves teams of Goldman partners interviewing each other about potential
candidates) are policies and practices that inherently discriminate against
women, particularly when those policies and practices are exercised within a
“boy’s club” culture, where for example, managers/decision-makers exclude women
from events such as barbeques, drinks, and golf outings, hire scantily dressed
female escorts to attend holiday parties, etc.
The Court first addressed Goldman Sachs’ attempt to use
“experts” in the financial industry to explain custom and practice for
evaluation and promotion; however, the Court rejected Goldman’s expert. In
United States v. Dukagjini, 326 F.3d 45, 54 (2d Cir. 2003), the Second
Circuit, interpreting the Daubert expert-certification
approach and applying Rule 702, held that expert testimony should be
excluded if the witness is not actually applying expert methodology. The
Honorable Judge Analisa Torres, writing in Chen-Oster
for the District Court, stated “[u]nder Daubert, the Court must
exercise its gatekeeping function accordingly, and ‘exclude unreliable expert
testimony and junk science from the courtroom.’” Chen-Oster, 2018 WL 1609267, at *8 (citing, inter alia, Almeciga v. Ctr. for Investigative Reporting, Inc.,
185 F. Supp. 3d 401, 415 (S.D.N.Y. 2016)). Judge Torres went on to state, “[g]eneral
knowledge about the financial services industry (or, indeed, uninformed
speculation about Goldman Sachs) could hardly be relevant or reliable on the
question of whether a statistician’s methodology is sound or supported.” Chen-Oster, 2018 WL 1609267, at *8. Judge
Torres specifically cited SEC v. Tourre,
950 F. Supp. 2d 666, 677–78 (S.D.N.Y. 2013), in which the Court had excluded
testimony because the expert’s knowledge and expertise was in “so broad a
category as to become meaningless when particularized” to the issues of the
case. Judge Torres, was emphatic: “Defendants cannot circumvent the
requirements of Rule 702 and Daubert by labeling a statistical
expert’s statistical exercises a ‘real world check.’ A wolf in sheep’s clothing
is still a wolf.” Chen-Oster, 2018
WL 1609267, at *8.
The Court also, recognizing the realities of large class
actions, allowed Plaintiffs to use “generalized proof” of statistical evidence
to show causation prima facie that Goldman
Sachs’ policies and practices have a disparate impact on women. Relying on Dukes v. Walmart, Goldman Sachs attempted
to argue that individual
managers applied Goldman’s practices in “highly individualized ways,” such that
Plaintiffs could not show that Defendants used a “common mode of exercising
discretion.” Id. at *12. But the Court “decline[d] to indulge in
Defendants’ semantic somersaults.” Id. Hitting
at the root, the District Court made clear that in Dukes the plaintiffs lost because they had not identified a “common
job evaluation procedure.” Here, Plaintiffs did. Id.
Defendants also, relying on a disaggregated business unit
argument, contended that gender
disparities were the result of “anomalies specific to individual Business
Units.” Id.
at *14. However, the Court rejected this argument, reasoning that “business
units” at Goldman Sachs were not fixed. Id.
For years, Goldman had transferred business units to different divisions, and
moreover, the personnel in those units regularly transferred to other units
and/or divisions. Id. Ultimately, the
Court found the Class expert’s cross-unit modelling of the correlation between
the performance/promotion process and gender to be persuasive, as it controlled
for, among other things, division, year, office, education, and experience. Id. at *15. The expert’s report thereby
provided significant proof of commonality for the purposes of showing the
disparate impact of Goldman Sachs’ practices on women.
The Court also certified
the disparate treatment claim, but not based on the Goldman Sachs “boy’s club”
culture. Interestingly, the Court applied a “statistics and anecdotal evidence”
approach in which it considered internal complaints, external complaints, survey
answers, emails, articles, business records, and declarations from class
members to ground
its disparate treatment analysis. While Courts may not be recognizing the
“boy’s club” phenomenon as evidence in and of itself, they are putting the
pieces together to show that misogynist attitudes and practices continue to
pervade certain workforces and injure women’s careers.
Although Dukes still
presents challenges, the Chen-Oster analysis is a boon to class
certification in discrimination cases.
If you have experienced discrimination based upon your gender, and need
help, contact Bryan
Schwartz Law.
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