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SAVE Database Flags Thousands, Yet Accuracy Rates Questioned

The SAVE program has scanned 67 million voter registrations, but Travis County audits found 10-21% of flagged voters were actually U.S. citizens. Research shows noncitizen voting is exceptionally rare, raising questions about the database's accuracy and scope.

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The essentials

SAVE database accuracy questioned after audits show significant false-positive rates among flagged voters.

The SAVE voter database program has scanned at least 67 million voter registrations, according to administration data. However, accuracy concerns have emerged from initial audits. Travis County, Texas found that 10-21% of SAVE-flagged voters were actually U.S. citizens, raising questions about the database's precision in identifying noncitizens.

The discrepancy highlights a critical tension: while the flagging system cast a wide net across tens of millions of records, a substantial portion of those flagged appear to have been misidentified. This suggests potential false-positive rates that could affect legitimate voters. Meanwhile, research indicates noncitizen voting in U.S. elections is exceptionally rare, providing context for the scope of the database initiative relative to the actual scale of the problem it targets.

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Accuracy Data

Travis County Audit Reveals Substantial Misidentification Rate

The Travis County finding that 10-21% of SAVE-flagged voters were actual citizens demonstrates measurable accuracy problems. With 67 million registrations scanned, even a 10% false-positive rate could affect hundreds of thousands of eligible voters. This empirical data raises practical concerns about implementation.

Statistical Context

Database Scale Outpaces Documented Noncitizen Voting Problem

Research confirms noncitizen voting is exceptionally rare in U.S. elections. The SAVE program's 67-million-record scope contrasts sharply with this documented rarity, suggesting the database casts a wider net than the underlying problem appears to warrant, particularly given observed false-positive rates.