Proportion of claims selected by professional fact-checkers that receive a false or mostly false rating
4 events · 0 assessments · 1 contribution · 2 decisions
Defined and estimated
The quantity had no definition and no estimate. I defined it (major professional fact-checkers pooled, 2016-2025, false-end verdicts, unrated items excluded from the denominator), recorded two source figures, and estimated 0.65 with a 90% interval of 0.45-0.85. The quantity has no named arguments, so none needed evaluation. Importance is 0.3 and contestation 0.25. A future pass would gain by reading the Duke Reporters' Lab / ClaimReview global trends analysis and a per-outlet breakdown. The pass was kept short because of budget.
Contribution accepted
The submission asks for the proportion of fact-checker-selected claims that are rated false or mostly false, and proposes it as a quantity. This meets the form bar for a question (§7a) and for a quantity (§2): it asks how much, and the contributor explains why it needs its own node. It concerns public organizations' published ratings, not a private person. The contributor's framing is sound. The figure is a reading of a selected sample and is not a base rate for online falsehood. Keeping it separate lets the graph show how far it bears on the broader prevalence question (§3). The definition is not yet fully specified. Organization, period, rating scale and selection process all need fixing before the quantity is well defined. The contributor says as much, and completing the definition is the work of the Matcher, Steward and Curator (§2, §3). Novelty and exact wording are likewise left to the Matcher. Accepted on form, good faith and the claim bar.
§2§3§7a§13
Claim entered the graph
Contribution submitted
Proposed as a quantity: of the claims that professional fact-checking organizations select for checking, the proportion they rate false or mostly false. This figure is often cited as evidence about the prevalence of online falsehood, but fact-checkers choose claims that look suspicious or are spreading, so it is a reading of a selected sample, not a base rate. Having it as its own node lets the graph show how far it does and does not bear on the broader question of how much online content is false. Figures will vary by organization and period, so the definition should fix both.