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Proofiness - Charles Seife [72]

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than richer citizens. (Especially since many white voters were exempted from paying the tax because of a “grandfather clause.”)71 As a result, the tax prevented many of them from voting.72 The states pretended that the taxes had a legitimate purpose—they were intended to raise revenue, and they argued that people who paid state taxes became more interested in furthering the state’s welfare. In reality, though, poll taxes were simply intended to keep African Americans from voting. Similarly, literacy tests were supposedly instituted to ensure that voters were able to make informed decisions; instead, they had the effect of barring less-educated African Americans from going to the polls. Legislators and judges eliminated these particular forms of voter suppression in the 1960s, but there are other more subtle forms that are still a problem. Voter ID laws, for example, are touted as a way to reduce voter fraud, as are periodic purges of voter registrations. However, there’s very good reason to believe that these measures are being enacted because they have the indirect effect of reducing the number of African-American, Latino, and other minority voters.

However, none of the forms of voter suppression are more effective or more insidious than one engineered by the Supreme Court. In a series of decisions, the Court dressed a mathematical lie in the mantle of truth, wiping millions of people out of existence with the stroke of a pen. Thanks to these rulings, more than 1 percent of the population of the United States consists of ghostlike disenfranchised creatures—citizens who in theory have the right to vote but are deliberately ignored. It’s a stunning case of proofiness that goes right to the heart of what democracy is all about.

This particular scheme has to do with manipulating the U.S. Census. This may not seem like such a sinister plot, but at its root, a democracy is a government based on counting—on counting its citizens and their votes. The founding fathers of the United States recognized the importance of counting to their new government. Indeed, only five paragraphs into the U.S. Constitution, there’s a passage that dictates that the government must perform an “actual enumeration” of its citizens every ten years. This decennial census is crucial to the functioning of the Republic, because it determines how much power different groups get to wield in the House of Representatives.

The 435 representatives in the House are divided (roughly) equally among the citizens of the United States—each representative nowadays votes by proxy for a block of roughly 700,000 people. The more citizens that a state has, the more representatives it gets, and the more power it wields in Congress. As the population shifts, political power (and money) follows. As the Northeast of the country atrophies, New York and Pennsylvania have been losing their preeminence to California and Texas. The political fortunes of a region—and of those who live in that region—hinge upon the results of the decennial census.

The government spends an ungodly amount of time and money to make an accurate count of its citizens; in 2000, the census cost roughly $6.5 billion—more than twenty dollars for each man, woman, and child in the United States. It’s an incredible undertaking, and it’s about as accurate as such a measurement can be. Unfortunately, the census, like any measurement, is fallible. And since the 1940s, statisticians have been forced to admit a depressing fact: no matter how hard census workers try, there’s a systematic error that they can’t get rid of. They can’t count everybody.

In some ways, the census is like a monstrous government-run poll, but there’s one very important difference. Instead of querying a sample of households and extending those results to the entire population, the census attempts to reach every single household in the United States; in theory, there’s no extrapolation needed. So, just as in the case of voting, there’s no statistical error. There isn’t any worry that a statistical fluke makes the census sample look different

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