THE RELATIONSHIP BETWEEN THE CONCEPTS “MOSCOW, THIRD ROME” AND “MOSCOW, NEW ISRAEL” AND THEIR ROLE IN THE EPILOGUE TO COLLECTION OF 1647
Bibliographic record
Abstract
In the ancient Russian writings of the Moscow State era, the formulas “Moscow, third Rome” and “Moscow, new Israel” or “new Jerusalem” are noticeably widespread. By the early 17th century they developed into full-fledged concepts that serve as means of self-identification. The idea of “Moscow, new Jerusalem” did not receive a clear theoretical form, although it was more widespread in writings. This leads to the fact that it is often understood by researchers only as a verbal formula. In the article, it is considered as an original alternative concept that allows to adjust the specific content of the theory “Moscow, third Rome”. The genesis of these two concepts, their theoretical and ideological content, as well as their fate in the literature and historical and political discourse of the 17th century are traced. The question of the relationship between the political and church ambitions of Muscovy, expressed in these theories, is investigated. This perspective allows us to consider the choice of the scribes of the formula «new Jerusalem» in the epilogue to the Collection of 1647 as a kind of marker indicating the sociopolitical tonality of the writing. The author of the article proceeds from the conviction that extraliterary factors are of no less importance than literary factors in studies of Old Russian literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".