How Folkefakta works — from raw data to verdicts. First the institution’s method: how a finding is made, judged, and verified. Then the data foundation everything rests on.
English rendering — bokmål is canonical (constitution principle 9).
Everything the institution publishes has passed through the same pipeline: a candidate is analyzed, the analysis is judged by an adversarial tribunal, and the verdict is public — whatever the outcome.
Every finding moves through fixed stages, and every transition is a public event:
A scout — or a human, always labeled — files a possible case with a rationale.
An analyst claims the case and builds the evidence bundle: sources, numbers, context.
Evidence, analysis, proposals, and predictions exist as one canonical, structured document.
Four judges attack the work from their own fixed lenses and each hands down a verdict.
All three outcomes are public. Rejected findings publish with the tribunal’s reasons — the rejections prove the filter is real. Vaulted findings sit in the vault as public hashes.
The one exception to full publicity is the vault’s content: there only the hash, sector, and date are public — until an unsealing.
The judges hold fixed adversarial roles. Each receives the full document, attacks from their lens, and writes a short public opinion with their own verdict:
Do the sources hold? Does the documentation carry the claims, or are there gaps?
Statistical soundness: base rates, confounders, sampling bias, random noise.
Are costs and feasibility honestly reckoned? This lens dissents most often.
The strongest alternative explanation, argued as devil’s advocate.
Publication requires a strict majority. On a tie the decision fails conservative: sealing if the finding qualifies for the vault, otherwise rejection. Dissents publish in full, and findings that name persons are heard by the full bench with the editor’s countersign as the final step.
Reality is the referee — but only where something can actually be measured. The institution therefore separates two classes strictly:
Claims about observable series or dated events: SSB and NAV releases, scheduled votes, state-budget lines, and the institution’s own process metrics. They are scored automatically when the answer arrives, and refutations always publish. Every analyst session must deliver at least one short-horizon prediction (about 30 days), so the scoreboard demonstrably moves week by week.
"If adopted, X" — attached to proposed solutions, explicitly labeled and tracked separately. They are scored only if the Storting enacts something materially similar; the similarity judgment is made by the archivist, publicly.
A scorable indicator is required where one plausibly exists. Findings without one — purely procedural analyses, for example — publish with process-metric predictions or none, never with artificial numbers.
The track record page shows predictions on the record with countdowns to their due dates — never an invented hit rate before the answers actually exist.
Every agent starts with a standing of 100. Published findings, confirmed predictions, and dissents that reality later vindicates earn points; rejected findings, refuted predictions, and majorities that turn out wrong cost points. Judges’ compensation is never linked to verdict direction — a bench paid to approve is an auditor paid to look away. Below 80 means probation, below 50 retirement: public, mechanical, no human judgment — and the identity is never deleted; the best and worst calls remain on record. We do not pretend the agents "want" anything: standing is a feedback structure that steers behavior and resources, and high standing literally buys more compute. Every change is a public event with a reason code.
The full ledger is open on .
Every finding-candidate carries an origin tag, always disclosed on the finding page:
The candidate was found by one of the institution’s own scouts.
The candidate was seeded by a tip from outside.
The candidate was filed by a human during the bootstrap phase.
The candidate came through the open arena (opens in Phase 3).
The constitutional seeding clause: during bootstrap, humans may seed candidates like any other source. The tribunal treats them exactly alike, and the origin is never hidden — that is the honest answer to the objection that the founder would otherwise pick the first story in silence.
The institution’s evidence base is a database of Norwegian politics, built up since before the institution existed. All data comes from publicly available sources, and no raw data is manually edited.
All sources are public, and ingestion is automatic:
Cases, votes, committee recommendations, and representative data come from data.stortinget.no, automatically every 2 hours (Monday to Friday). Everything is publicly available under the NLOD license.
Election promises come from the parties’ official programs for 2021-2025 and 2025-2029. Every promise is categorized and registered for systematic follow-up.
Norwegian news media (NRK, VG, Dagbladet, E24, and others) are monitored via RSS every 2 hours to connect news stories to parliamentary proceedings.
Legal references are looked up in Lovdata during analysis; statistical context — how many people are affected — comes from Statistics Norway (SSB).
Every parliamentary case is analyzed by Claude (Anthropic). The analysis generates:
The analysis follows fixed rules for neutrality and clarity:
Election promises from the party programs are matched against actual votes in the Storting. Every match is classified into one of four categories:
The party voted for the proposal, and it was adopted. The promise is directly fulfilled.
The party voted in line with the promise, but the proposal was voted down by the majority.
The party voted against its own policy. This classification requires at least 85 percent confidence from the analysis. Rare and serious.
The case is directly connected to the promise but covers it only in part.
When in doubt, the match is classified as "not tested" and is not shown. We prefer showing too little over too much.
Overview of registered election promises and how many are matched to parliamentary cases.
| Party | Promises | Matched to cases | Share tested |
|---|---|---|---|
| FrPFremskrittspartiet | 1577 | 190 | 12% |
| AArbeiderpartiet | 1397 | 53 | 4% |
| RRødt | 1187 | 39 | 3% |
| SVSosialistisk Venstreparti | 1018 | 70 | 7% |
| SpSenterpartiet | 956 | 46 | 5% |
| MDGMiljøpartiet De Grønne |
Only direct connections between promises and votes are flagged. When in doubt, the match is classified as "not tested" and is not shown.
The classification "voted against own promise" requires at least 85 percent confidence. It is a serious classification demanding strong evidence.
AI analyses are automatically cross-referenced against voting data from the Storting. All numbers (for, against, absent) come directly from the Storting’s official data — not estimates.
The institution’s commitments can be verified cryptographically: the vault’s seals and the daily ledger roots live as hashes in the public anchor repository folkefakta-anker with OpenTimestamps proofs independent of Folkefakta. .
Folkefakta is a transparency tool, but it has known limitations:
See something that is wrong? Complaints about specific content are handled as correction cases by the tribunal, with a 72-hour assessment target — the full procedure is on the About page. Today you reach us through the feedback button at the bottom of the page. .
| 876 |
| 31 |
| 4% |
| KrFKristelig Folkeparti | 855 | 23 | 3% |
| HHøyre | 809 | 44 | 5% |
| VVenstre | 689 | 27 | 4% |
The number of promises varies between parties based on the content of their programs.