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Dispatches From the New Jim Crow

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This is just flat-out election theft:

Recently, there’s been an uproar about Georgia’s approach to voter registration. The state’s “exact match” law, passed last year, requires that citizens’ names on their government-issued IDs must precisely match their names as listed on the voter rolls. If the two don’t match, additional verification by a local registrar will be necessary. The Georgia NAACP and other civil rights groups have filed a lawsuit arguing that the measure, effective since July 2017, is aimed at disenfranchising racial minorities in the upcoming midterm elections.

Georgia Secretary of State Brian Kemp, a Republican who is running for governor against Democrat Stacey Abrams, has put on hold more than 53,000 voters so far, given mismatches in the names in their voting records and other sources of identification such as driver’s licenses and Social Security cards. If the measure takes effect, voters whose information does not exactly match across sources will need to bring a valid photo ID to the polls on Election Day to vote. That could suppress voter turnout, either because some voters lack IDs or because voters are confused about whether they are eligible. Proponents of the rule assert that it is only meant to prevent illegal voting.

[…]

Georgia’s records had a higher proportion of exact matches than we found nationwide — but 30 percent of actual voters still failed to exactly match in that state.

By contrast, using our algorithm, which correlates with L2’s in-house matching records nearly perfectly (r=.99), we are able to match almost 127 million registered voters — or 93 percent of all voters in the 2014 data. Among those whose records did not exactly match, we found that 25 percent have at least a 99 percent probability of being correct matches, while 28 percent have at least a 95 percent probability.

Using our algorithm, in other words, 91 percent of those on Georgia’s voter rolls would be cleared to vote, or 3,941,342 voting-eligible citizens — while “exact matching” clears only 70 percent, with the potential of disenfranchising 909,540 eligible citizens if no additional checks are conducted.

I also attempted to link the voters in the 2016 American National Election Study (ANES) with voter records contained in the L2 data using two methods: exact matching, and an improved version of fastLink I recently developed.

The results appear in the chart below. As you can see, the “exact matching” method misses a substantial share of valid matches. While our algorithm validated 60 percent of the voter records, “exact matching” validated less than 30 percent, on average.

And in keeping with the concerns of opponents of the Georgia measure, nonwhite voters are especially likely to be harmed. The match rates using exact matching are nine and six percentage points lower for black and Hispanic voters, respectively, than for white voters.

As the philosopher Mike Mularkey once said, they’ll keep doing it until it stops working.

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