21-09-2025, 06:53 PM
I’ve been running paragraph-level topic models on the text. The first passes (NMF/LDA) made it clear that a lot of variance is explained by style-language A/B and scribal hands. However, the plots also showed sharp colour changes exactly at section boundaries (e.g., Herbal → Pharma), suggesting that genuine themes coexist with stylistic effects.
To separate the two, I cleaned the text (removed single-character tokens and a small, empirically derived list of near-ubiquitous “stop-forms”) and switched to DMR (Dirichlet-Multinomial Regression). In DMR the topic word distributions are global, while the topic mixture for each paragraph depends on covariates (here: language, writing hand, Currier). In practice this lets style influence how much of each topic appears without redefining the topics themselves. I compared several K topic numbers and selected K=6 (highest AMI between topics and editorial sections). Here are the topic distributions through the folia and separated by section, language, writting hand and currier hand:
![[Image: v6tNPxL.png]](https://i.imgur.com/v6tNPxL.png)
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The six topics align as follows:
![[Image: D01thGY.png]](https://i.imgur.com/D01thGY.png)
Distribution. Heatmaps and stacked timelines show near-pure blocks per section: Zodiac/Astro→T1, Pharma→T2, Biological→T4, Herbal→T5, Marginal→T0, Text/Cosmo→T3. Where sections change, the dominant topic usually flips at the same boundary.
![[Image: Zs1DuKt.png]](https://i.imgur.com/Zs1DuKt.png)
Language and hands. Language and hands still influence prevalence. Language A leans Herbal (T5); Language B spreads over T0/T1/T3/T4. Some hands show long runs dominated by one topic, yet topic shifts track section changes. This points to thematic structure that is not merely scribal style.
![[Image: 4wnRjm9.png]](https://i.imgur.com/4wnRjm9.png)
A cautious reading is that this patterning is inconsistent with pure gibberish: the DMR analysis (K=6) uncovers stable, section-aligned topics whose vocabularies persist across scribes and languages, suggesting the text carries systematic content rather than random noise.
I would appreciate any comment.
To separate the two, I cleaned the text (removed single-character tokens and a small, empirically derived list of near-ubiquitous “stop-forms”) and switched to DMR (Dirichlet-Multinomial Regression). In DMR the topic word distributions are global, while the topic mixture for each paragraph depends on covariates (here: language, writing hand, Currier). In practice this lets style influence how much of each topic appears without redefining the topics themselves. I compared several K topic numbers and selected K=6 (highest AMI between topics and editorial sections). Here are the topic distributions through the folia and separated by section, language, writting hand and currier hand:
![[Image: v6tNPxL.png]](https://i.imgur.com/v6tNPxL.png)
[size=1]
[/size][size=1][size=1]
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[/size][/size][/size]The six topics align as follows:
- T0 – Marginal stars: qok-… with -ain/-ey; dominant on the marginal-stars pages.
- T1 – Astronomical/Zodiac: frequent -iin/-ar/-ey; peaks in Astronomical and Zodiac.
- T2 – Pharmaceutical: ch/che- + -ol/-or (e.g., chol, cheol, cheor), plus qok+-ol; strong in Pharma.
- T3 – Text/Cosmological: general high-frequency forms (ar, or, aiin…); Text-only and parts of Cosmological.
- T4 – Biological (balneological): distinctive -edy/-dy with qo-/qoke-/oke-; the balneological block.
- T5 – Herbal: ch/sh + o/l patterns; Herbal pages, especially in Language A.
![[Image: D01thGY.png]](https://i.imgur.com/D01thGY.png)
Distribution. Heatmaps and stacked timelines show near-pure blocks per section: Zodiac/Astro→T1, Pharma→T2, Biological→T4, Herbal→T5, Marginal→T0, Text/Cosmo→T3. Where sections change, the dominant topic usually flips at the same boundary.
![[Image: Zs1DuKt.png]](https://i.imgur.com/Zs1DuKt.png)
Language and hands. Language and hands still influence prevalence. Language A leans Herbal (T5); Language B spreads over T0/T1/T3/T4. Some hands show long runs dominated by one topic, yet topic shifts track section changes. This points to thematic structure that is not merely scribal style.
![[Image: 4wnRjm9.png]](https://i.imgur.com/4wnRjm9.png)
A cautious reading is that this patterning is inconsistent with pure gibberish: the DMR analysis (K=6) uncovers stable, section-aligned topics whose vocabularies persist across scribes and languages, suggesting the text carries systematic content rather than random noise.
I would appreciate any comment.


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