КНЯЗЬ ВАСИЛИЙ ИВАНОВИЧ РОСТОВСКИЙ-БЕЛОГОЛОВ ПРОТИВ КНЯЗЯ ДМИТРИЯ АКСАКА БЕЛЬСКОГО И ТРЕТЬЯКА ВЕЛЬЯМИНОВА: ИВАНГОРОДСКИЕ СТРАДАНИЯ НА РУБЕЖЕ XVI и XVII вв.
Bibliographic record
Abstract
Статья посвящена практикам воеводского управления в приграничных городах московского Северо-Запада в период между окончанием Балтийских войн и Смутой. Два конфликта воеводы князя Василия Ивановича Ростовского-Белоголова со своими товарищами демонстрируют специфику распределения властных полномочий между воеводами, отчасти – принципы воеводского назначения и вместе с тем – этические основания службы московского служилого человека конца XVI – начала XVII в. на фоне сложностей управления приграничным транзитным Ивангородом. The article is about the practices of voivodeship governance in the border towns of Moscow’s North-West between the end of the Baltic Wars and the Time of Troubles. Two conflicts between Prince Vasily Ivanovich Rostovskij-Belogolov, the voivode in Ivangorod, and his deputies demonstrate the specific distribution of authority between voivodes, partly the principles of voivodeship appointments, and moreover, the ethical fundamentals of the Muscovite servicemen at the turn of the 16th and early 17th centuries, on the backdrop of the complexities of governing the border transit town of Ivangorod.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".