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Use three checks: pin down exactly what was said, trace the number to its original source and understand what it measures, then test whether the evidence supports the speaker’s conclusion. A statistic can be accurate while the comparison or conclusion built around it is misleading.
1. Capture the exact claim before checking it
Save the full statement, who made it, when and where it was said, and the surrounding context. Look for the original transcript, video, official post or press release rather than relying on a clipped repost or a summary. A few missing words can change whether a speaker made a factual assertion, expressed an opinion or described a trend.
FactCheck.org says it reviews political transcripts, videos, websites, press releases and social-media statements. It also says, of its own process, “The burden is on the person or organization making the claim to provide the evidence to support it.” That describes the organization’s approach; it is not a universal legal rule. FactCheck.org’s process is a useful example of tracing a claim to its source.
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2. Separate measurable facts from opinions
Some parts of a political statement can be checked directly: a date, a quotation, a reported statistic or a description of what a policy document says. Other words need a standard before they can be assessed. “Unemployment is high,” for example, is incomplete without a benchmark: high compared with when, where or what level?
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“Wages are too low” combines a measurable question—what are wages, and how have they changed?—with a value judgment about what counts as enough. Data can inform that judgment, but cannot settle it by itself. The House of Commons Library’s guide to checking facts emphasizes distinguishing fact from opinion and giving claims their context.
3. Trace the statistic to its original source
Find the named statistic, dataset, report or calculation, then follow it back to the organization that produced it. A politician’s graphic or a news article may be a useful lead, but the underlying release or data table lets you inspect the definition and notes directly.
- For U.S. employment figures: the Bureau of Labor Statistics (BLS) is an original source for labor-market data.
- For U.S. national economic accounts: the Bureau of Economic Analysis (BEA) publishes measures such as gross domestic product and personal income.
- For a UK labor-market claim: the Office for National Statistics (ONS) is an example of a primary statistical source identified in UK parliamentary guidance.
- Elsewhere: use the relevant national statistical agency or another well-documented primary source for the jurisdiction being discussed.
These agencies serve different jurisdictions and measure different subjects; do not treat one country’s source as authority for another country’s figures. FactCheck.org’s process page gives the U.S. BLS and BEA as examples of source agencies. For broader advice on finding official information and recognizing stripped context or altered media, see the European Commission’s guide to finding information you can trust.
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Ask whether the number actually measures what the speaker says it does. A figure about one group, region or period may not support a claim about the whole country or a different period. Check the measure’s definition, population, geography, dates and units; for wages, establish whether figures are nominal or adjusted for inflation. Then check that any comparison uses equivalent measures and time spans.
For “unemployment is high,” identify the unemployment measure and choose an explicit comparison—for example, a specified earlier period or a comparable place. Without that benchmark, “high” is a characterization, not a conclusion established by the number alone.
The UK Office for Statistics Regulation (OSR) offers five practical questions for evaluating statistics used in election claims:
- Do the statistics seem wildly unlikely or too good to be true?
- Does the claim logically follow from the statistics quoted?
- Is the source for the figure in the public domain?
- Has the figure been quoted without any context or background?
- Where comparisons are made, are they comparing like-for-like?
The OSR published these questions in guidance on 25 March 2026 in the UK election context; the checks can still help readers assess claims elsewhere. See its statistics guidance.
5. Read the release notes and check for revisions
A published economic estimate is not always final. Check the release date and version, any revision notes, and whether the source explains assumptions or incomplete source data. If two figures come from different release vintages, that may explain a discrepancy; it does not automatically mean either source is unreliable.
The U.S. BEA’s Information Quality Guidelines describe how it provides information about source data, methods, assumptions, planned updates and revisions, and studies estimate accuracy over time. Those details matter when deciding whether a figure is settled or directly comparable with an earlier release.
6. Distinguish a trend from a cause
“This happened during the administration” describes timing. “This happened because of the administration” makes a causal claim. A before-and-after change or correlation alone does not establish that a policy caused an economic outcome; many factors may contribute.
For a causal claim, look for evidence connecting the policy to the outcome, note the assumptions behind that analysis, and consider plausible alternative explanations. The descriptive number may be clear even when the cause remains uncertain. If the evidence establishes only that two things changed together, say that rather than presenting causation as proven.
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When reputable sources or analyses disagree, compare what each actually covers rather than treating disagreement as proof that all figures are suspect. Check:
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- the measure’s definition and population covered;
- the time period and data-release version;
- the geography and data source;
- the method and assumptions;
- whether the figure is observed, estimated or forecast; and
- whether the conclusion is descriptive, comparative or causal.
Different measures can capture different aspects of the economy and show different trends. Explain those differences, link to the underlying data or documents, and use independent corroboration where relevant. The Commons Library describes Full Fact’s practice of aiming for two sources for a central claim unless only one is relevant, with a preference for primary data tables and legal documents. Full Fact’s published advice, quoted in that guide, is: “We’d prefer you not to. Anything we publish is attributed and linked to its source, so you can make your own mind up about it.”
A practical checklist for your next claim
- Save the complete original statement, its speaker, date and context.
- Mark which parts are verifiable facts and which depend on a value judgment or undefined word such as “high.”
- Locate the original statistic or document and confirm the correct agency for the country and subject.
- Match the measure, dates, population, geography and comparison to the exact wording.
- Read methods, assumptions and revision notes; identify the release version.
- Separate what happened from claims about why it happened.
- Compare relevant independent evidence, link the sources and describe unresolved differences.
- Conclude in calibrated terms: accurate, inaccurate, unsupported, or misleading because important context is missing.
This method evaluates a particular statement; it does not decide every claim about a policy or economy in advance. Official statistics are primary evidence for what an agency measured, while interpretation still depends on definitions, assumptions and context.
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