A quarter century ago, thousands of Black and Latino teachers brought a discrimination case against New York City. The Second Circuit probed Thursday whether an algorithm should guide how damages are doled out.
MANHATTAN (CN) — The first batch of awards in a discrimination case that the New York City Board of Education has faced for the last 25 years went before the Second Circuit U.S. Court of Appeals on Thursday.
It was in 2012 that U.S. District Judge Kimba M. Wood found the city liable for giving prospective teachers a racially biased literacy test that caused qualified Black and Latino applicants to lose jobs, wages, benefits and seniority status.
No longer challenging whether it must pay — the Second Circuit affirmed liability in 2014 — the city takes issue now with how a court-appointed special master has determined damages for the individual educators. There are 347 teachers, out of a total of more than 4,500, slated to receive the first awards.
As it stands, the judgment for this group representing less than one-tenth of plaintiffs totals more than $170 million in back pay and other relief, plus pension liability.
Richard Dearing, assistant corporation counsel for New York City, argued on behalf of the BOE this morning that these teachers by now have accumulated two decades of work history, making the calculation of damages a difficult one.
His brief says the full amount, which could total hundreds of millions, will yield a “large and unjustified windfall” to the teachers, violating Title VII’s goal of making victims whole.
At oral arguments, Dearing blamed the calculation on a misunderstanding of the so-called “wrongdoer rule,” which he emphasized is “not a basis to achieve an unrealistic aggregate result for the class.”
In contrast to “back-of-the-envelope calculations” for each individual, as he called it, Dearing noted that statistical models have been used to calculate hundreds of awards and, if used here, would have avoided “mucking around through this quagmire for some period of time.”
Such a model would also account for the probability of a prospective teaching being hired, and how long the teacher would have worked for the BOE. Dearing pointed out in his brief that the city did not hire 25% of comparable prospective teachers who passed the literacy test — the Liberal Arts and Sciences Test replaced the Core Battery exam in 1993 — and 50% of those who were hired left their posts within 10 years.
Using those metrics to reduce the awarded back pay would be more reliable than what has become a “proxy war about credibility,” he said, relying on teachers to sit down and consider ups and downs of daily work life over several decades, among myriad other factors — including discrimination they may have faced at work.
Joshua Sohn, an attorney for the teachers, rejected the idea that, because the BOE “discriminated against so many people, and for so long,” that it is now “entitled to a discount” on damages.
He said Dearing’s statistical model suggestion would use a “blunt instrument” of a 25% discount, something “unsupported by evidence or legal precedent.”
Of the 1,738 judgments entered so far, 357 plaintiffs were not awarded back pay, Sohn said. And of the plaintiffs awarded back pay, 46% did not receive the full pay accrual through the date of judgment.
Sohn also noted that some teachers retired or died during the decades-long procedures, ending their damages calculation, which would not have been accounted for in a blanket statistical model.
The BOE could have protested the individualized awards process earlier, but instead, “they waited to see how it turned out,” said Sohn, of the firm Stroock & Stroock & Lavan.
Attorneys made their arguments peppered with questions from U.S. Circuit Judges Robert Katzmann, Raymond Lohier and Susan L. Carney. The panel reserved judgment.
Neither Sohn nor New York City’s legal department responded to requests for comment.
The Liberal Arts and Sciences Test was discontinued in 2004. Judge Wood found in 2015 that the test’s successor, LAST2, used from 2004 to 2012, was also racially biased.