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By: Shane Miller
Recently in Stouffer v. Union Railroad Company, LLC, No. 22-1680, (3d Cir. Oct. 26, 2023), the Third Circuit Court of Appeals issued a precedential decision that serves as a useful reminder about the importance of statistical evidence in disparate impact cases. Because such evidence is so critical, parties to a disparate impact lawsuit should consider hiring a statistical expert early on to help shape their claims and defenses.
A disparate impact case differs from a typical employment discrimination lawsuit. In a routine case, the employee claims that their employer intentionally treated them less favorably due to age, race, or another protected trait. To prevail, the employee must prove that the employer had a discriminatory intent or motive. This is called a disparate treatment theory of liability.
Disparate impact lawsuits follow a different framework. In these cases, the employee alleges that the employer adopted a rule or policy that seems fair but has the effect of harming a protected group, such as older workers, racial minorities, and so forth. The U.S. Supreme Court first recognized disparate impact as a valid legal theory more than 50 years ago in Griggs v. Duke Power Company, 401 U.S. 424 (1971). Just a few years earlier, Congress had enacted the Civil Rights Act of 1964, which prohibits employment discrimination based on race, color, religion, sex, and national origin.
From the outset, Title VII clearly barred a covered employer from adopting explicit discriminatory policies, such as refusing to hire racial minorities or women. But in Griggs, the employer did not impose such a blatantly illegal policy. Instead, the employer instituted a rule that all employees must have a high school diploma to hold certain jobs. A group of African American employees alleged that this policy was merely a subtle way for the company to relegate them to the lesser jobs. Since they were less likely to hold high school degrees, they had a lower chance of obtaining the good jobs at the company.
When the case reached the U.S. Supreme Court, the Court sided with the employees. The Court ruled that Title VII prohibits not only intentional employment discrimination but also practices that seem fair on their face but that are discriminatory in practice. The Court held that if an employment practice operates to significantly exclude or harm a certain group and is not related to job performance, it is prohibited by Title VII even if the employer had no discriminatory motive or intent. Since then, disparate impact has been a viable legal theory in employment law cases. And in these cases, both parties usually rely on statistical evidence. The employee asserts that the statistical evidence proves that an employment policy significantly harms a protected group, while the employer tries to prove the opposite.
The Stouffer case shows how this works in practice. The employee, a 41-year old man, worked for a railroad company. The company fired him for a safety violation. He sued, claiming that it had a policy of discriminating against older workers by disciplining them for minor infractions, placing them on last-chance agreements, and then firing them for minor violations. The Third Circuit, however, rejected the employee’s claims and dismissed his lawsuit with prejudice (meaning permanently). Although the employee alleged that the company’s policy had a “statistically significant” impact on older workers, the Third Circuit found that he provided no specific statistical evidence or factual allegations to back up his claims. So, although disparate impact cases have been alive and well for more than 50 years, the Stouffer decision serves as a useful reminder that statistical evidence remains critical in these cases. Since the outcome likely turns on statistical evidence, a party to a disparate impact case should consider retaining a statistical expert early on to help guide their strategy.