Fighting Back—In Triplicate
One man's battle with the bureaucracy
When government tries to do good, there is more to it than first meets the eye. One of the many indirect effects of programs aimed at righting wrongs concerns the collection of data. Whenever government says, "Let there be more x," for example, it can't simply stop there. It has to go ahead and find out where x is lacking, the rate of change of x, and the phases, modes, and moods of x; for until some numbers are gathered, injunctions can't be issued, nor can the dollars flow.
As government mandates the accomplishment of ever-more abstract and diffuse social "goods," the burdens and perplexities of data collecting grow accordingly. This point is perhaps nowhere so clearly demonstrated than in what are euphemistically called "affirmative action" programs. In these programs, the government's aim is to enforce preferential treatment for selected social groups. The major problems with this idea are well known: unfairness, lowering of standards, invasion of privacy, loss of personal freedom, lowering of institutional morale and effectiveness, and a heightening of social tensions and stereotypes—members of the favored group are presumed to be unable to qualify on their own merits.
Less noticed, however, are the problems of data gathering. In order to decide where to punish and where to reward, bureaucrats must collect numbers to justify their actions. From afar, this task may seem simple and straightforward. Only when you get into the process of actually attempting to collect affirmative-action compliance data does the expense and absurdity of the effort become apparent. And sometimes, absurdity is the best rejoinder to absurdity.
I first encountered the data-collecting problem several years ago as a member of the recruitment committee for the department of political science at the university where I teach. After the committee's job was completed and the positions filled, the chairman of the department came to me with an unusual request: would I submit a tabulation of the numbers of ethnic minorities and women in the recruitment pool of some 200 applicants?
Well, I could have labored over the two feet of file folders, attempting to deduce such data from stereotypes. Maybe this Howard Jefferson from Southwest Alabama Tech was black. Maybe that Thea Rolkolsky who wrote a dissertation on "Prejudice against Women in the Sung Dynasty" was female. Perhaps this Jack Harishii-Al was a member of a favored minority.
But, I figured, a scholar ought not to operate this way. There was nothing to do but wing it. I simply made up some numbers, typed them out neatly on departmental letterhead, and passed them along to the chairman. (One can't say my numbers were biased, by the way. I knew the Feds could hit us either way. If the numbers were too small, why weren't we making an effort to enlist the favored groups to enter our applicant pool? If they were too large, why hadn't we hired more of the favored groups with so many to choose from?)
My "objective guess" was passed along to higher levels, duly collated with other such racial and sexual statistical data, and eventually laid at the feet of the vengeful gods in Washington—forming, no doubt, the basis for subsequent complaints or suits against the university.
Sometime later, I had another brush with affirmative action, in the form of a survey from Duke University. This time I was being asked, not whether someone else had a favored status, but whether I had. The survey form was sent to me because I run a tiny publishing outfit (so tiny that its yearly losses hardly depress my standard of living), and in 1978 Duke University kindly purchased one of my books—for the princely sum of $3.85 (plus shipping). Three years later, in 1981, the long arm of affirmative action reached into that transaction. The form from Duke University read as follows:
Duke University is in the process of updating and validating its vendor files and your help is needed.
The attached questionnaire will be used to assist us in monitoring our procurement dollars in compliance with Public Law 95-507; therefore, your cooperation is necessary for our compliance efforts.
Please check the appropriate box. We certify that we are (as defined in DAR 1-700-1-700, 14 + 7-104.14):
? Small Business ? Large Business ? Small Business owned and controlled by socially and economically disadvantaged individuals.
We certify that we are:
? More than 50% Female owned.
? In an Eligible Labor Surplus Area.
It quickly occurred to me that this questionnaire was probably only the first small snowflake. I had sold books to hundreds of colleges and universities over the years. If all the schools made a dutiful, law-abiding effort to comply with PL 95-507, the questionnaires coming my way would soon swell into a full-blown blizzard. I'd better try to do this first one right, I thought.
I went to work on the questionnaire with a will. I checked the first box, "Small Business," without hesitation. Being very sharp on logical traps often laid in questionnaires, I cleverly avoided checking the "Large Business" box.
The next item was perplexing. Surely there were many senses in which I was both "socially and economically disadvantaged." Many find me rude, and I'm not the friendliest guy in the world. We still don't have a color TV. And one of my colleagues pointed out that I was not a member of the Briarcrest Country Club. (My wife thereupon argued that I hadn't tried to join—but that was, I said, because I couldn't afford it.) On balance, I decided to check the third box.
Female ownership? I scratched my head. Three of the four members of our family are female—and Texas is a community-property state. Check.
In an Eligible Labor Surplus Area? Did they mean at the time that I made the sale, or now, or at some future date? Maybe DAR 1-700-etc.—whatever that was—would answer the question, but I wasn't about to hire a lawyer to have it unearthed. Besides, the idea was creeping up on me that checking boxes (except, of course, "Large Business") was a smart thing to do: if I put enough A+'s on my report card, Duke University might be forced to buy my entire stock!
I signed the form, dated it, and mailed it back. And then I sent Duke University the bill for my consulting fee for filling out the form—$385.00. I figured that if Duke, the federal bureaucracy, and the US Congress had decided this information was worth the thousands of man-(and person-) hours they were obviously putting into collecting it, the price should reflect a source of quality and distinction. Otherwise, people might begin to suspect that affirmative-action statistics are simply a phony game to dupe the credulous—and to keep the rest of us too busy to care.
Several weeks later, I received both a long-distance phone call and a two-page letter from an uptight "Assistant Contract Administrator" at Duke who failed even to suspect I might be joshing him. They had sent out, he wrote, 10,000 such forms and were horrified at the idea of paying for the "answers." Loath to sever the endless skein of red tape, however, he invited me to further clutter up his desk by replying "in writing within fifteen (15) days from the date post marked on this envelope."
But enough was enough. When someone doesn't get a joke, you don't explain the punch line.
James L. Payne teaches at a major university in the southwestern United States.