47
Suhas Subramanyam
Serving in office
Scheduled research active
Main board
Too little promise evidence has been reviewed. Treat this score as provisional.
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: 0 x 0.8
- Partial delivery: 1 x 0.4
- Never delivered: 3 x 0.0
- Disputed claims tracked separately: 0
- Reviewed promises in current record: 6
- Confidence: 33%
- Current claim count: 13
- Current evidence count: 26
Office History
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U.S. Representative
Virginia 10th · current
Historical elected offices still need research.
- Protect federal civil servant and contractor jobs in Virginia's 10th Congressional District.
- Support manufacturing in the United States, invest in infrastructure, and strengthen the middle class.
- Always support the right to in-vitro fertilization and a woman's bodily autonomy.
- Continue to advocate for campaign finance reform.
- Fight restrictive voter ID laws, protect early voting, and combat political gerrymandering.
- Continue to support Medicare's ability to negotiate drug prices.
- Take steps to expand access to mental health care providers.
- Support responsible regulation of blockchain technologies.
- Protect Medicare, Social Security, and veterans benefits.
- Establish mandatory recovery time objectives for federal data across federal agencies and require the Department of Defense to submit a data recovery strategy.
- Require publicly traded companies to review and disclose whether any of their products may have been produced with Uyghur forced labor.
- Direct the Department of Homeland Security to develop a strategy and recommendations to protect communities near data centers and other data infrastructure, including transmission and water infrastructure.
- Establish a $10 million per year grant program to support UAS pilot training for fire departments, emergency medical service providers, and law enforcement agencies.
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.