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Political fact-checking can be carried out by crowd workers, providedthey are supervised by experts. We propose a Bayesian latent variable ordinal probitmodel for truthfulness rating data, to estimate workers’ reliability, weigh in their con-tributions, and surrogate expert judgments. This is a notable example of aggregationfunction of an implicit type. This method may be used to dynamically assign workersto new tasks, as illustrated with an analysis of PolitiFact data.