Zipf in the Chancery

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)

Assyriology, sitting on hundreds of thousands of digitized tablets, learned to treat administrative writing as a statistical population: text types and formulae in the Ur III archives follow heavy-tailed frequency distributions with stable shape parameters. Medieval English charters, digitized in the DEEDS corpus, are the parchment descendants of the same activity — routine bureaucratic record-keeping — but they are studied as diplomatic specimens, not as a distribution. I conjecture that the rank-frequency distribution of diplomatic formulae in DEEDS charters follows the same distributional family, with a shape parameter statistically close to the Ur III value, despite three thousand years, two languages, and a change of medium from clay to sheepskin. The mechanism is that bureaucratic text production is a preferential-reuse process — scribes copy the formula they saw last — and such processes converge on the same heavy-tailed law regardless of substrate. If this holds, documentary cultures have a universal production grammar, and deviations from the curve become a new instrument for detecting chancery reform.

Prediction clause (verbatim)

Rank-frequency distributions of diplomatic formulae extracted from the DEEDS charter corpus will be better fit by a lognormal than by a pure power law (Vuong likelihood-ratio test, p < 0.05), and the fitted shape parameter will lie within 20% of the corresponding value computed from Ur III administrative formulae in BDTNS. Primary clause (the verdict follows it): the lognormal-versus-power-law model selection outcome on DEEDS. Secondary clause: the cross-corpus shape-parameter agreement within 20%.

Kill-dataset (verbatim)

The DEEDS corpus of dated medieval English charters, with BDTNS (Database of Neo-Sumerian Texts) as the cuneiform comparator; kill is a statistical test (Vuong model-selection test and parameter comparison).

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 with zero tool use, emitted as a single JSON text message per the fresh-lane blindness protocol.

Novelty / leakage triage

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

Formula-frequency analysis of DEEDS charters is the project's core dating methodology (Gervers; Feuerverger et al. 2012), so the corpus is heavily operationalized, but the rank-frequency distributional-family fit (lognormal vs power law) and the cross-corpus shape comparison to Ur III formulae in BDTNS are un-run.

Predictions

No prediction registered yet.

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