The illusion of truth found in statistics is that numbers not only point at truth, they actually touch it. When I was a boy growing up in the cornfields of Southern Illinois, my two mentor grandfathers would take me rabbit hunting. They would put me in middle as the three of us walked in a line down the rows of winter stubble in the harvested field. If we scared up a rabbit, and the two of them missed both left and right, they proclaimed by an average of their two missed shots, I had hit the rabbit. Statistically, that I had not even pulled the trigger made no difference, though we at no rabbit for dinner that night.
So here’s the philosophical question: if 59,000 employees do not take their meal or lunch breaks, but no one sees or hears a manager tell them to forego their breaks, does the missed break really happen? Actually, the question is legal as well, and has practical consequences. The employees would like to use statistical proof to make their case. The proof goes like this: if the employer’s time records show an unexpectedly high incidence of missed breaks so far outside the “standard deviation” expected by random chance, then can we conclude that another factor was operating to produce the missed breaks? And . . . is that other “factor” the culture and direction of management?
Currently, the California Supreme Court is considering this question, somewhat differently articulated. Plaintiffs are suing a restaurant chain in the case of Brinker v. Chili’s, Romano’s Macaroni Grill and others for penalties associated with missed breaks for tens of thousands of employees. The Court of Appeal rejected the statistical evidence, and denied class status on the grounds that there was not sufficient commonality among the employees. Each employee, held the court, had a unique question of fact as to why the break was not taken. The question arose because the Brinker court also ruled that an employee could recover for missed breaks only if the employee proved that management required the employee to work through the break, or knew of the practice of missing a break, and passively condoned the practice.
The issue will be decided by a court having new Brown appointments to the Bench, and in the aftermath of conservative Dukes v. Wal-Mart, the recent U.S. Supreme Court decision rejecting the “culture of bias” theory proven by sampling data. Chief Justice Tani Gorre Cantil-Sakauye and Justice Goodwin Liu have been appointed by Governor Jerry Brown, and likely will had a liberal bent to the Court as it revisits the issue. My prediction however is that the “tail” will “wag the dog” in this case. That is, I think the court will hold that a) employers have no automatic liability for missed breaks they fail to monitor and enforce but also b) that statistical evidence will be deemed admissible as proof of the issue that employers are actively preventing employees “as a class” from taking their breaks. That is, the statistics will be admissible to prove employer complicity and intent, similar to the way statistics operate in “disparate impact” cases in discrimination filings.