The notary launders the vowels

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)

Phonetic misspellings — iotacisms, dropped finals — are the audible fingerprints of ordinary Greek, and the Duke Databank encodes tens of thousands of them as editorial regularizations. A private letter preserves its writer's noise; a petition by the same person was usually drafted by a professional whose office orthography scrubbed it clean. So the corpus should show the same senders oscillating between noisy and clean text depending on document type — proof that spelling in the papyri measures who held the pen, not how the named party spoke. If it holds, orthographic 'vulgarity' statistics stop being social history of speakers and become a map of scribal intermediation.

Prediction clause (verbatim)

For individuals attested as senders of both private letters and petitions in papyri.info (matched via Trismegistos People, n>=20 pairs), regularization density (editorial reg/corr markup per 100 words) is at least 50% higher in their letters than in their petitions. Primary clause: that paired difference — a matched-sample statistical test.

Kill-dataset (verbatim)

papyri.info (DDbDP regularization markup) with Trismegistos People links.

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

Generated blind by claude-fable-5 in a single Write from the inline prompt alone, with no file reads, web access, or database queries.

Novelty / leakage triage

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

The PapyGreek/Sematia programme explicitly connects DDbDP regularization markup to scribal intermediation and social variation, and Vierros showed notaries mask parties' language, but the matched-sender letters-vs-petitions regularization-density test is un-run.

Predictions

No prediction registered yet.

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