53
Juan Ciscomani
Serving in office
Scheduled research active
Main board
The signal is improving, but the lifetime record is still thin.
This profile keeps a lifetime office and promise record. The trust score is designed to stay close to 50 until enough claims and evidence are reviewed.
Breakdown
- Delivered during the term promised: 2 x 1.0
- Delivered in a later elected term: 2 x 0.8
- Partial delivery: 5 x 0.4
- Never delivered: 1 x 0.0
- Disputed claims tracked separately: 0
- Reviewed promises in current record: 10
- Confidence: 45%
- Current claim count: 10
- Current evidence count: 41
Office History
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U.S. Representative
Arizona 6th District · current
Current federal elected office. Term began in January 2023 after the 2022 general election. -
U.S. Representative
Arizona 6th · current
Historical elected offices still need research. -
Candidate for U.S. Representative
Arizona 6th District
Federal reelection campaign for the same U.S. House seat. The FEC election page confirms the 2024 district contest and incumbent status. -
Candidate for U.S. Representative
Arizona 6th District
Federal campaign for the U.S. House seat; successful 2022 cycle that led to his current office.
- I will be an independent voice fighting for the people of Arizona's 6th District.
- I will listen directly to constituents and act on the issues that matter to them.
- I will fight to secure the border.
- I will fight to cut Washington's spending addiction.
- I will support policies that make American energy dominant and independent.
- I will fund and support law enforcement, the military, and veterans.
- I will give parents a say in their child's education.
- I will continue campaigning in every corner of the district and reach everyone in the district.
- I will oppose any and all efforts to raise taxes.
- I will use my first vote in Congress to remove Nancy Pelosi as Speaker.
Method note
Long term, this app should score against a manually reviewed promise ledger that spans every elected office the candidate has held. The current model uses a Bayesian-style shrinkage step: thin records are pulled back toward 50 so the UI does not overstate certainty.
Claim occurrences, evidence, and future AI adjudications are all designed to store provider and model provenance. Formula version: 0.1.0.