One of the latest in the seemingly endless rounds of alarming statistics is that one out of 12 American children has some form of disability. With all the things that are supposedly getting worse, you have to wonder how our life expectancy keeps increasing. A cynic might even wonder if the increasing availability of money from the government has anything to do with the increasing number of "problems" that need to be "solved" by government programs.
One way of telling whether a given statistic is a fact or an artifact is to ask whether the definition used fits the thing that is being defined. Buried in the news story about the children with disabilities is the fact that the definition of "disability" has been expanding over the years.
A child who is likely to be diagnosed as autistic today might not have been some years ago. Yet that is seldom mentioned in alarming statistics about the escalating number of cases of autism. As the author of a couple of books about late-talking children, I hear regularly from parents who tell me that they are being asked to allow their children to be labeled "autistic," in order to get either the government or their insurance company to pay for speech therapy.
It is amazing that, with something as serious -- indeed, catastrophic -- as autism, statistics are thrown around without mentioning the variation in what is being diagnosed as autism. In something much less serious, such as sales receipts at Wal-Mart, a comparison of how much money was taken in this year, compared to last year, will almost certainly make a distinction between sales receipts at the same stores as last year versus sales receipts that include new stores opened since last year.
In other words, they notify you of changing definitions behind the numbers. Otherwise, the statistics could mean almost anything. If it is important enough to do this for Wal-Mart sales, it certainly ought to be important enough to do it for autism.
Regardless of whether the old or the new criterion for autism is better, they are different criteria. Statistics should tell us whether or by how much autism has risen by any consistent standard. Moreover, those who diagnose autism range from highly trained specialists to people who never set foot in a medical school.
Another set of statistics whose definition is at least questionable are statistics about the incomes of high school dropouts versus those who have more education. Since most high school dropouts resume their education at some later time, are these statistics really counting all -- or even most -- dropouts? Or just the minority of dropouts who never enter a classroom again?
Although I dropped out of high school more than half a century ago, and still do not have a high school diploma, I do have a couple of postgraduate degrees. Is my income counted when they add up the incomes of dropouts? Not bloody likely.
This is not just a fine point. All sorts of efforts are being made to prevent kids from dropping out of high school, as if dropping out means the end of their education. Since it usually means only an interruption, leading eventually to a resumption of their education after some experience in the real world, the urgency of preventing them from encountering the real world is by no means obvious. They may be more serious students afterwards.
One of the most brazen uses of statistics which do not fit the definition was in a much-praised book that attempted to show that black students admitted to colleges under affirmative action do just fine. The book was titled "The Shape of the River," written by William Bowen and Derek Bok, former presidents of Princeton and Harvard, respectively.
Although this book is crammed full of statistics, not one of those statistics is about black students admitted under affirmative action. Black students admitted under the same standards as white students are lumped together with black students admitted under lower standards. Yet, from this the authors conclude that affirmative action is a good thing -- to the applause of those who apparently wanted to see that conclusion more than they wanted to see meaningful statistics.
Advocates of campaign finance reform often speak of the corrupting influence of money. But they seldom include the corrupting influence of the government's money on what statistical "facts" are fed to the public.