I’m on the verge of retiring from my job as a technical editor for the National Oceanic and Atmospheric Administration here in Juneau. It has been a good career, and I’ve had some great colleagues over the years who gave me a healthy respect for the work of government.
During my early years at NOAA, there was one job in particular that presented me with an intellectual challenge as a writer and gave me a real appreciation for the work of public service.
It was 1996, my second year on the job. I had cleared my desk and went walking through the halls calling out, “Work! Give me work! I need work! ” And someone yelled out, “Give him the overfishing definition.” And you could hear people chuckling in their offices all up and down the hall. When you go looking for work, you get the job nobody else wants.
The job was this: someone had to write a public notice explaining a new overfishing definition. The Magnuson-Stevens Act requires that federal fisheries be managed sustainably, so we have to define “overfishing,” the point at which so many fish have been removed from a population that the stock can no longer sustain itself. Because we cannot actually count the fish, we are always more or less uncertain about the size of a species’ population. NOAA’s fisheries scientists had therefore created a new overfishing definition that contained several pages of ultra-sophisticated statistical formulae for determining the extent of our uncertainty about the precise overfishing level.
Now, these pages of ultra-sophisticated statistical formulae can be understood only after decades of advanced study and with 24-hour support from an emergency team of people who have PhDs in biometrics and are high on formaldehyde fumes.
And math and I have never been particularly close to begin with. When I attended college in the free-wheeling 1970s, colleges were reevaluating whether they should be educating us students or just giving us a place where we could run around naked for four years and consume various hallucinogens. This allowed me to spend four years reading poetry and hanging around the college pub arguing with feminists about Norman Mailer’s weltanschauung. It also allowed me to avoid taking any math.
But I like a challenge, so I started digging in. Faced with pages of ultra-sophisticated statistical formulae, I was determined to understand every stupid variable.
For two weeks I immersed myself. I surrounded my computer with textbooks on statistics and biometrics. I spent hours on the phone with statisticians and scientists at the Alaska Fisheries Science Center — beautiful people all, and brilliant. But I just wasn’t getting it.
After two weeks, I felt no closer to understanding it all. Throwing my hands up in frustration, I left the Federal Building and went for a walk in the rain.
I was walking up Basin Road when suddenly I got it: I realized what the statistics were saying. I virtually ran back to the office and in two hours had drafted an explanation in simple terms, terms even I could understand, of how these statistics helped us understand how certain or uncertain our assessment of the size of a stock’s population and thus would allow us to manage the fisheries carefully, cautiously, sustainably.
(For the hopelessly curious, that explanation is inscribed for posterity in Volume 61 of the Federal Register, pages 54145-54147.)
Rather than explain the formulae variable-by-variable, which might just lead readers into a hopeless quagmire of equations, I opted to describe how the formulae operated. I finished the draft and sent it off in an email to the Big Brain who cooked up this stuff — a lovely Vulcan of a man named Grant Thompson. (May you live long and prosper, Grant Thompson, wherever you are.)
The next day, Grant gave me a call, which went something like this:
“Hi, Jim. I read your draft, and, well, you know, your explanation doesn’t really ... well, I mean, it does sort of, I guess, maybe, in a way, but, well, not really, I mean not precisely, but kind of, sort of, you know, after a fashion, I suppose. I’m not sure that, well, you know, really I don’t think… no, I guess, you know, I think… maybe… maybe it does, maybe it will do, in a way, yes, but you know…. No, no, no…I think it’ll do. Yes. Let’s go with this. Good. Yes. Thanks. Okay. Later.”
And I realized how Moses felt.
Here’s my idea of the back story to the Book of Genesis: God comes to Moses and explains it all — the Big Bang, Schrödinger’s cat, the general and special theories of relativity, plate tectonics, evolution, punctuated equilibrium — the works.
But Moses, you know, he lived a thousand years before the invention of science. He doesn’t have a clue what God’s talking about. His brain is still reeling when he tries to explain to people what God said: “Well, first there was kind of a big light, you know, and then the earth and, oh wait, first the sky and then the earth, yeah that’s it, and then the oceans. And then, let’s see… oh yeah, then the animals, and then the people.… And voila! That’s how it all happened!”
The next day, he gets a call from God: “Hi, Moses. I read your draft. . . .”
And maybe Moses didn’t explain everything precisely the way it had been explained to him, but he did the job he needed to do: he explained the cosmos in a way that let his readers know that the universe made sense, even in the face of all their uncertainties. And that’s all they wanted.
My description of the overfishing definition may not have explained the statistics precisely enough to satisfy a scientist, but it wasn’t inaccurate, and it did the job it had to do. It explained to non-scientists — to fishermen and other normal people — how it made sense that we manage the fisheries this way in the face of all our uncertainties.
That’s when I fell in love with public service.
• Jim Hale can be reached at www.jimhalewriting.com