The prompter's ear misspells

Status: Anticipated · untested

Status is derived only from the shepherd-authored triage/prediction data above -- community submissions and claims are a separate overlay and can never change it (see the participation panel below).

This is a proposed connection between two domains, generated by a language model. It is not an article and not evidence: it sits below the evidence/publication boundary. A quantitative prediction and a named kill-dataset are attached (when registered) so the claim stays falsifiable rather than merely evocative.

Claim (verbatim)

Dunhuang preserved both pristine devotional sutra copies and scrappy popular performance narratives, the bianwen or 'transformation texts'. The connection is that which errors a manuscript makes reveals which organ it passed through: a text written from dictation, memory, or oral checking substitutes homophones (right sound, wrong character), while a text checked eye-against-exemplar confuses similar-looking graphs. Performance texts, living in the mouth, should carry a loud phonetic error signature; sutras, produced by visual collation, a graphic one — and scribes made it so involuntarily, because no one can fake their channel's error profile. If this holds, hundreds of unlabeled Dunhuang narrative fragments can be assigned to the performance circuit or the library by their misspellings alone.

Prediction clause (verbatim)

Classify scribal errors in bianwen and in dated sutra copies from the same deposit as phonetic (homophone substitution) or graphic (visually similar character). Primary clause, which decides the verdict: the phonetic share of errors in bianwen exceeds the phonetic share in sutra copies by at least 20 percentage points. Secondary clause: within bianwen, phonetic errors outnumber graphic ones by at least 2 to 1.

Kill-dataset (verbatim)

IDP, the International Dunhuang Programme: its digitized bianwen and transformation-text manuscripts alongside dated sutra copies from the same caves, worked with the published error collations.

Nobody has run this test. The kill-data is named above. If you can run it — or you know the paper that already settles it — claim the kill or submit the prior. Kills and priors are credited here, by name, as they come in.

In the atlas

This conjecture is bridged, as an L1 lead, onto these Inferpedia subject pages.

Provenance

Run: Fresh agent generation · model: claude-fable-5

Composed blind by claude-fable-5 from internal knowledge with zero tool use and emitted as a single text message.

Novelty / leakage triage

anticipated in the literature — this exact test has never been run

A Ghent project is explicitly analyzing phonetic loan characters in non-canonical Dunhuang manuscripts as a marker of orality, and paleographic studies distinguish phonetic vs graphic substitutions — the mechanism is anticipated. The decisive comparative census (phonetic error share bianwen vs dated sutra copies, 20-point gap) is unpublished.

Predictions

No prediction registered yet.

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