(17-06-2026, 06:27 AM)Jorge_Stolfi wrote: You are not allowed to view links. Register or Login to view....
The "off by one" pattern is interesting — but it doesn't require scribal error. At the stroke level, "r" and "n" are both word-final single strokes occupying the same position. Mauro's distributional analysis confirms that "r" and "n" behave similarly in word-final context. The parallel frequency series between "ir"/"iir"/"iiir" and "iin"/"iiin"/"iiiin" reflects the fact that adding "i" strokes before either word-final stroke produces a parallel series — because both endings occupy the same structural position. No misreading required.
Regarding cho (91) / sho (138): even this "reversal" confirms the relationship rather than refuting it. 91 and 138 are the same order of magnitude — compare this to natural language, where visually similar words like "the" and "thy" differ by a factor of 10,000. In the VMS, even the reversed pair differs by a factor of 1.5. And exact constant ratios across all pairs would require a counting mechanism, a scribe tracking frequencies and maintaining precise proportions. The variation in ratios — 1.2 here, 2.8 there, occasionally reversed — is the human signature. The ratios are approximately proportional because the process is approximately consistent. The imprecision is the proof that a human produced the text, not an algorithm.
Moreover, "cho" doesn't exist in isolation as a pair with "sho." It exists in a network and is therefore also similar to "cheo," "chol," "chor," "chy," and more. The frequency of "cho" reflects its entire network position — how many similar words exist, how often each is visible, how often each is used as a source. Isolating one pair and demanding its ratio match another pair's ratio ignores the network that determines all frequencies simultaneously.
Regarding Hamlet: self-citation is not a universal text generator that could produce any text. It makes specific predictions through the feedback loop inherent in the copying process: frequent words are more likely to be selected as copying templates, generating more variants; the existence of more variants increases the probability that members of that word family are selected in subsequent copying events. This feedback loop predicts specific features:
- Frequency-connectivity correlation: the most frequent words accumulate the most similar neighbors.
- Continuous evolution: each new word differs minimally from its source; accumulated modifications produce gradual vocabulary drift — the "chol" to "chedy" gradient.
- Asymmetric vocabulary distribution: "words typical for Currier A exist in Currier B, but not the other way round" (Timm & Schinner 2020, p. 8) — because late-emerging variants could not appear on pages written previously.
- Near-identity of type and token word length distributions: since each new word inherits the length of its source, the type inventory mirrors the token distribution.
- Prefix-suffix independence: prefix and suffix are selected independently from visible sources.
- Spatial clustering: similar words co-occur on the same pages (+95%) and paragraphs (+123%) because they are generated from the same visible sources (quimqu).
Hamlet has none of these properties. Self-citation predicts all of them. The VMS has all of them.