Statistical Impact of Disproportionate Age Discrimination at Lawrence Livermore Lab

Statistical Impact of Disproportionate Age Discrimination at Lawrence Livermore Lab *************************************************************************************************************************************** The plaintiffs in Phase II of our trial Andrews v. Lawrence Livermore National Security, LLC (LLNS) have suffered emotional distress, humiliation, and feelings of inadequacy as a result of their illegal layoffs from Lawrence Livermore Lab (LLNL) in 2008. The disproportionate layoff of workers age 40+, leading to disparate age discrimination at LLNL, can be illustrated through statistical analysis. To that end, plaintiff’s expert witness, statistics Professor William Lepowsky, came to the conclusion that the odds of so many older employees, over age 40, being laid off were “1 in 1,091,000.” The emotional and statistical significance of this layoff are at the heart of our case. Andrews vs. Lawrence Livermore National Security, LLC is a unique case that began with Judge Robert Freedman separating the trial into two Phases. Phase I focused on breach of contract and breach of implied covenant of good faith and fair dealing at LLNL. Our plaintiffs prevailed in Phase I with an award of $2.7 million for plaintiffs Elaine Andrews, Marian Barraza, Mario Jimenez, Greg Olsen, and James “Rocky” Torrice. Statistician: Professor William Lepowsky Professor Lepowsky has taught statistics and mathematics for 45 years at Laney College in Oakland, California. He is not a professional expert witness, like the statistician hired by LLNS defense team, but rather a professional educator with an esteemed background. Professor William Lepowsky’s qualifications include: B.A., Harvard College 1967; Major Mathematics M.A., U.C. Berkeley 1968; Department Mathematics (graduated summa cum laude) M.A., U.C. Berkeley 1976; Department Statistics Qualified as expert witness to testify in the California court system and the Federal courts “Statistical Significance” Key to Disproportionate Age Discrimination One of the most important aspects of Andrews v. Lawrence Livermore National Security, LLC is the utilization of statistical analysis brought forth by Professor Lepowsky. Professor Lepowsky’s statistical analysis illustrates that LLNS discriminated against older workers, 40+, during the layoff in 2008. To this end Professor Lepowsky utilizes “statistical significance” the probability that an effect is not likely due to just chance alone. Lawrence Livermore Lab’s Faulty Layoff Unit Statistical Analysis The basis for LLNL’s statistical argument was their creation called the Layoff Unit. 273 Layoff Units were created by LLNS line managers, the decision makers in the layoff process, as a means of grouping employees. Layoff Units were not recognized within the rules for layoffs or within the plaintiff’s contracts. According to Professor Lepowsky, the Layoff Units do not accurately represent the layoff in 2008. A few of the characteristics of LLNS Layoff Units: Nearly 20% of the 273 Layoff Units (48) had only one employee More than 25% of the 273 Layoff Units (72) had only one or two employees Nearly 50% of the 273 Layoff Units (125) had five or less employees 30% of the employees that were classified in Layoff Units were assigned to 1% of the Layoff Units Statistical Analysis Process In Professor Lepowsky’s statistical analysis, Layoff Units were not used. Instead, Professor Lepowsky utilized the following process in his statistical analysis: Workforce: 40% of the workforce was not eligible for layoff. These “excluded” workers were chosen solely by LLNS line managers. Professor Lepowsky identified who could be laid off Comparison: compare “like” employee positions such as physicists with physicists and engineers with engineers Where Workforce Worked: identify where the workers work and which line managers they worked for at the lab Job Code: group workers by the same job code Classifications: group and classify workers by directorate, division, or department Vital to the analysis is the fact that every employee analyzed by Professor Lepowsky is tied to a decision maker, line manager at the lab. The disparity of sizes of the Layoff Units, used by LLNS in their analysis, was a major reason why Professor Lepowsky did not accept the Layoff Unit analysis. The importance being the fact that Layoff Units did not compare employees with like characteristics. Statistical Significance Points to Age Discrimination The following are key statistics and information that support the assertion that disproportionate age discrimination was prevalent during the 2008 Lab layoff. According to Professor Lepowsky, the exclusion process favored employees under the age of 40 to a statistically significant degree and it hurt employees over the age of 40 to a statistically significant degree. The statistical impact is evident within the numbers. Excluded Employees: line managers chose who would be excluded or safe from the layoff. Of those excluded as of May 22, 2008: 54.1% were 39 years old or younger and 40.6% were 40 years old or older Excluded Employees Standard Deviation: of all employees analyzed by directorate, division, or department at all levels the layoff had a statistically significant impact on employees over the age of 40. Ranging from 3.34 to 4.09 well above the agreed upon 2.0 Standard Deviation Layoff Policy: the “different employees, different policies” assertion by LLNS is not correct. There was one layoff with specific rules that were broken by LLNS 1 in 645,000: the probability (chance) that older workers in Directorate and Job Code were “over selected” for layoff if the process of layoff equally impacted young and older workers. Equal to 4.66 Standard Deviations 1 in 1,091,000: the probability that older workers in Division and Job Code were “over selected” for layoff. Equal to 4.77 Standard Deviations 1 in 76,000: the probability that older workers in Department and Job Code were “over selected” for layoff. Equal to 4.20 Standard Deviations Termination Percentages: 6.6% of employees 39 and younger were terminated vs employees 40 and older who were terminated at a rate of 11.5% In the final analysis according to Professor Lepowsky, “The disparity between old and young in selection rates (for layoff) is statistically significant.” ********************************************************************************************************************************************** Gwilliam, Ivary, Chiosso, Cavalli, & Brewer If you are interested in information regarding this case or If you suspect that you, have been the victim of workplace age discrimination, wrongful termination, harassment, or retaliation please contact attorney J. Gary Gwilliam or attorney Randall E. Strauss of the law firm of Gwilliam, Ivary, Chiosso, Cavalli, & Brewer at (510) 832-5411 ext. 233 or GGwilliam@giccb.com