Ship It
Gerald Pemberton had counted everything for twenty-three years. Unemployment rates to the third decimal place. Labor force participation by demographic quintiles. Seasonal adjustments that kept America’s economic pulse steady and predictable.
His cubicle at the Bureau of Labor Statistics was positioned precisely between the water cooler (visited 4.7 times daily, average) and the emergency exit (never had been used). His lunch—turkey sandwich, apple, string cheese—eaten at same time every weekday. His coffee mug bore the faded logo of the 2019 Federal Employee Health Fair.
Gerald lived for the beautiful mundanity of data. Numbers didn’t lie, didn’t cheat, didn’t suddenly decide to leave you for a yoga instructor named Brad.
But today, staring at the preliminary employment report, Gerald’s hands trembled. The cursor blinked at him mockingly. Someone—three levels above his pay grade—had changed the seasonal adjustment methodology. The real unemployment rate wasn’t 3.8%. It was 6.2%.
Millions of discouraged workers, vanished with a malicious sleight of hand.
Gerald’s supervisor, Marvin, appeared at his shoulder. “Looks good, Pemberton. Ship it.”
“But the methodology—”
“Ship it.”
Gerald stared at his screen. Twenty-three years of meticulous, honest work. His pension was eighteen months away. His mother needed her medications. His cat, Mr. Whiskers, required prescription kidney food.
His finger paused over the ‘Submit’ button.
Then Gerald Pemberton, GS-12 Statistical Analyst, did something unprecedented. He saved the file to a flash drive, deleted it from the server, and walked to the emergency exit.
For the first time in twenty-three years, someone used it.
Outside, Washington buzzed with its usual chaos. Gerald fumbled for his phone, scrolling to the contact labeled “Washington Post - Econ Reporter.”
His thumb shook as he typed: “I have something you need to see.”
The earth didn’t actually shake. But for Gerald, who had spent his life counting other people’s certainties, uncertainty felt like freedom.