13-08-2024, 12:17 PM
@Torsten:
My apologies for attributing to you a prediction that you did not make; and my thanks for planting a different idea. Would not self citation necessarily obey one-way causation of textual novelty—as you describe—but on other scales? On individual pages we have some confidence about the order of composition, and a scribe could not have cited words that they had not yet created. The MMED plot for your simulated text clearly shows this causal horizon progressing down the pseudo-pages. The trend would be baffling if observed in a conventional "linguistic" text.
Of course texts generated by human computers will contain various confounds, but their past will not have been affected by their future, so we potentially could find telltale indicators of citation-with-variation in their time-ordered output. My first-attempt plot for Takahashi pages is not definitive... but if a refined treatment (with a better autocorrelation function, more appropriate transcription, whatever) were to find a statistically significant slope, then I would be statistically significantly persuaded that you are on the right track.
I fully agree that the value of SelfCitationTextgenerator lies in the clarity of its function, not the verisimilitude of its output. That is precisely why we can attribute downpage MMED increase to self citation in this one case. An eighth-order correlation matrix generates impressive midline Voynichese, with adjacent-word phenomena and all, but is less useful as a research tool.
@Emma May Smith:
Your reasoning that word mutations must eventually converge on a statistically equilibrated vocabulary appears to be borne out by Torsten's simulated text. Parsing it into 45 pages of 26 lines each,
generated_text.txt
MMED values for the first 15 lines are not exactly as before, since now fewer pages are co-averaged. Truly random scatter could be lowered by processing a larger sample, but the finite vms will require a sharper tool.
@oshfdk:
You are right to recommend that tools invented for the vms should be tested on non-mysterious samples; Torsten's procedurally simulated text seemed to be the most relevant last night. Although Early Modern English is not highly inflected, I do have the 1611 King James Bible suitably formatted. Treating each of the 89 Gospel books as a page, and computing MMED relative to their first verses,
1611 King James Gospels
The word-scrambled results (open markers) give some impression of the inherent statistical noise. As expected (?) no trend is evident. The absolute values for a Finnish or classical Latin text will indeed be different. It is interesting to consider what kind of document, at what levels of organization, would deviate strongly from zero slope.
My apologies for attributing to you a prediction that you did not make; and my thanks for planting a different idea. Would not self citation necessarily obey one-way causation of textual novelty—as you describe—but on other scales? On individual pages we have some confidence about the order of composition, and a scribe could not have cited words that they had not yet created. The MMED plot for your simulated text clearly shows this causal horizon progressing down the pseudo-pages. The trend would be baffling if observed in a conventional "linguistic" text.
Of course texts generated by human computers will contain various confounds, but their past will not have been affected by their future, so we potentially could find telltale indicators of citation-with-variation in their time-ordered output. My first-attempt plot for Takahashi pages is not definitive... but if a refined treatment (with a better autocorrelation function, more appropriate transcription, whatever) were to find a statistically significant slope, then I would be statistically significantly persuaded that you are on the right track.
I fully agree that the value of SelfCitationTextgenerator lies in the clarity of its function, not the verisimilitude of its output. That is precisely why we can attribute downpage MMED increase to self citation in this one case. An eighth-order correlation matrix generates impressive midline Voynichese, with adjacent-word phenomena and all, but is less useful as a research tool.
@Emma May Smith:
Your reasoning that word mutations must eventually converge on a statistically equilibrated vocabulary appears to be borne out by Torsten's simulated text. Parsing it into 45 pages of 26 lines each,
generated_text.txt
MMED values for the first 15 lines are not exactly as before, since now fewer pages are co-averaged. Truly random scatter could be lowered by processing a larger sample, but the finite vms will require a sharper tool.
@oshfdk:
You are right to recommend that tools invented for the vms should be tested on non-mysterious samples; Torsten's procedurally simulated text seemed to be the most relevant last night. Although Early Modern English is not highly inflected, I do have the 1611 King James Bible suitably formatted. Treating each of the 89 Gospel books as a page, and computing MMED relative to their first verses,
1611 King James Gospels
The word-scrambled results (open markers) give some impression of the inherent statistical noise. As expected (?) no trend is evident. The absolute values for a Finnish or classical Latin text will indeed be different. It is interesting to consider what kind of document, at what levels of organization, would deviate strongly from zero slope.
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