Tuesday, July 27, 2010

Former TV News Anchors Lose Age Discrimination Claims Due to Insufficient Statistical Evidence

Two former local San Francisco television news anchors had their age discrimination claims dismissed by a California federal district court after their statistical evidence was deemed inadequate to establish that they were either replaced by substantially younger employees with equal or inferior qualifications or discharged under circumstances otherwise giving rise to an inference of age bias.

Interesting about this case is the plaintiffs' use of statistical analysis to show the court that is was improbable that age didn't have a factor in the decision to terminate them given the employer's allegedly neutral lay-off plan:
Lepowsky’s report shows that the age of KPIX’s on-air talent correlated closely with defendant’s decisions regarding whom to fire. In fact, for all twelve analyses he conducted, the pvalues were less than 1.58%, indicating a relatively high degree of statistical significance. In the scenario with the least correlation (analyzing the actual ages of the employees, excluding Rodgers and including the five anchors), Lepowsky concluded that “[i]f age were not a factor in the selection of the five (5) individuals to be laid off, then there is only a 1.58% probability (or a 1 in 63 chance) that the mean age of the five (5) laid off individuals would be as great as it was . . . .” Lepowsky Report at 10. Lepowsky found that the situation with the greatest correlation (analyzing age ranks, including Rodgers, but excluding the five anchors) had a p-value of 0.21%, and would occur by chance only once every 476 times. Id. at 17. All the other scenarios fell between these two extremes.
However, the court held that precedent revealed that "the Ninth Circuit’s 'unexplainable on grounds other than age' standard has meant that plaintiffs relying solely or even primarily on statistical evidence have been unable to satisfy the prima facie case," but "[i]n the few cases in which statistical evidence aided a plaintiff in establishing a prima facie case, the plaintiff bolstered his claim of discriminatory intent with other pieces of non-statistical evidence." The district court noted the problem with this precedent:
A consequence of the Ninth Circuit’s development of this area of law is that, for lawsuits in which a plaintiff seeks to use statistical evidence as the primary support for his prima facie case, the three-step McDonnell Douglas analysis collapses into a single step. Specifically, where a plaintiff’s statistical analysis fails to preemptively account for a defendant’s legitimate, non-discriminatory reason for discharge, the statistical results cannot show “a stark pattern of discrimination unexplainable on grounds other than age.” Not only does this state of affairs require that plaintiffs put the proverbial cart (pretext) next to or before the horse (prima facie case), it places reduction-inforce plaintiffs, who frequently must rely on statistical evidence of discriminatory intent, at a distinct litigation disadvantage.
Despite noting this disadvantage to plaintiffs who use statistical evidence, the district court also noted that it is bound by precedent of the 9th circuit and held the statistical evidence in this case "...does not account for defendant’s legitimate non-discriminatory justification, ... [and] falls short of establishing 'a stark pattern of discrimination unexplainable on grounds other than age.'" On the disparate impact claim the court ordered additional briefing by the parties to determine whether summary judgment is also proper. The gender discrimination claim was also dismissed.

The case is Schechner v CBS Broad Inc., NDCal, July 14, 2010.

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