Methodology

How PartyLine Works

PartyLine turns official roll call data into clear, issue-level voting records with no commentary or spin.

How It Works

Three simple steps to find politicians who actually vote the way you think.

Share Your Views

Answer quick questions about where you stand on key issues like healthcare, climate, immigration, and more.

We Analyze the Records

We compare your positions against real congressional voting records for incumbents, and against clearly labeled estimated public-position data for challengers when no voting record exists. Challengers for whom we have no substantive public evidence are shown as “No score yet” rather than given an overall score derived from party alone. Where we do show a challenger, individual issues we have no direct evidence on fall back to their party’s typical position and are labeled “(est.)”. That is the majority of challenger issue rows today, so read any challenger position without a cited source as an estimate rather than something that candidate said.

See Your Matches

Discover which politicians vote the way you would, with issue-level breakdowns and key vote context.

Data Sources

For incumbents: VoteView for historical roll call votes; the Congressional Research Service, via Congress.gov, for the official summary of what each bill does; the House Clerk and Senate roll call feeds for the official text of each vote; and the Bioguide directory for member metadata.

For candidates: Ballotpedia, FEC donor data (DIME/CFscores), and VoteView records for anyone who has previously held federal office. Most candidates have little or no such evidence; where that is the case we say so on their card rather than implying we found something.

For officeholders outside Congress: state legislator rosters come from Open States, covering the 50 states plus DC and Puerto Rico. Mayor rosters come from Wikidata, joined on Census place codes: they are sourced and checkable, but not yet hand-verified against each city’s own records, so treat a mayor listing as believed-current rather than confirmed.

How Votes Are Categorized

AI models analyze bill text, titles, and summaries to assign each vote to a primary issue category. This ensures legislation is grouped consistently across sessions.

Issue Scoring

Each incumbent issue score is calculated from categorized roll call votes using a significance-weighted averaging system. Landmark votes count more than minor votes, purely procedural votes are excluded from issue scoring, and the final score reflects long-run voting direction on that issue over time.

Our vote records run from 1981 to the present with no missing years. For a period they did have a gap: the 114th Congress — all of 2015 and 2016 — was absent from every member's record, because VoteView writes one column differently for those two years and our reader silently skipped all 622,405 rows of it. 538 members had a two-year hole in the middle of their record. It was found and backfilled on 25 August 2026, and a test now fails if any year between 1981 and today goes empty again.

Scores range from 0 to 100. One end of the scale reflects one side of the debate; the other end reflects the opposite position. Scores in the middle reflect mixed voting behavior. Challenger scores are published separately as estimated positions. Where a challenger has real public evidence — a campaign site, a Ballotpedia profile, a recorded position — we use it and link it, but that is the minority of what we hold: across the candidates a reader can currently reach, 28.6% of issue rows rest on real evidence, 64.7% are a party-affiliation baseline, and the remaining 6.7% have no recorded source — rows we can attribute to neither real evidence nor a party label, and we count them as neither. A baseline is a starting point drawn from party, and it says nothing about that particular person. So a challenger must have real positions on at least three issues before we publish a number at all — today 41% of reachable candidates show “No score yet” instead of a number that could imply false precision. Each issue page describes what the two ends of the spectrum represent for that specific topic.

Update Cadence

Recent votes are ingested through a scheduled update pipeline, and the data freshness is tracked so new roll call votes can be added shortly after they occur.

AI Transparency

First, where AI is deliberately absent. The plain-English description of what a bill does is copied word for word from the official Congressional Research Service summary. No AI writes it. Where no official summary exists, we show nothing at all rather than a plausible guess — today that is 218,290 vote receipts carrying verbatim official text and 27,780 deliberately left blank. An automated check re-verifies every published summary against its official source on every update.

We used to generate those summaries with AI. In August 2026 we measured a sample against primary sources, found 37.9% of them contained invented claims, and removed the generator rather than trying to tune it.

For incumbents: AI does two jobs. It classifies the dominant policy issue of each bill so votes group consistently, and it assigns each vote's direction — which side of an issue a “Yes” counts for. Direction matters most, because getting it backwards would invert a politician's score rather than merely misfile it. Both are reviewed against primary sources, corrections are recorded permanently with their evidence, and votes whose direction cannot be established are excluded instead of guessed at. AI never alters a vote outcome; those come from the official record.

For candidates without voting records: AI models (Google Gemini for initial categorization, Anthropic Claude for evidence re-scoring and off-topic filtering) estimate issue positions from Ballotpedia profiles, campaign materials, and other public sources — where those sources exist. For most candidates they do not, and no AI is involved in what happens then: the remaining issues take a party-affiliation baseline, which is arithmetic on a party label and not an estimate about the person. These estimates are clearly labeled and scored separately from vote-derived data. Claude also re-audits incumbent vote categories and directions — a second model checking the first.

Where an AI-estimated position can be verified against harder evidence (FEC donor data, or a VoteView record for a candidate who previously held office), the verified data takes precedence.

How we know this

Every caveat on PartyLine links here. This is what each one means — and why showing uncertainty beats hiding it.

What a “receipt” is

Every position we show traces back to specific roll-call votes a politician actually cast. Each one links to the official record on congress.gov, so you never have to take our word for it.

“Based on N votes”

The count next to a position is how many votes it rests on. A position built on 3 votes is real but thin — three votes leaning the same way produce a “strong” score by simple arithmetic. That is why we always show the number: you decide how much weight it deserves.

“Insufficient data”

It means exactly that: this person has not cast enough scoreable votes on this issue for us to state a position. We say “we don’t know” instead of guessing — a missing number is survivable; a confidently wrong one is not.

“Party estimate” and “(est.)”

Some candidates have no voting record yet. Where we show anything for them, it is their party’s typical position — a starting guess, clearly labeled, never presented as something they personally did. The moment real votes exist, the estimate is replaced by the record.

No Commentary. No Spin.

PartyLine is designed to organize voting data, not persuade. Every issue score is backed by public records and surfaced transparently.

Explore the Data

Explore the issue library to understand definitions and directional scoring, or take the survey to see your top matches.

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