THE FORMATION OF THE LATIFUNDIA OF THE PRINCES OF ZASLAV IN VOLHYNIA (TO THE END OF THE SIXTEENTH CENTURY)
Bibliographic record
Abstract
The article examines the formation of the latifundia of the Princes of Zaslav in Volhynia from the mid-fifteenth to the late sixteenth century, tracing how relatively cohesive princely domains emerged from dispersed clusters of settlements. On the basis of act books, the family archive within the Sangushko collection, materials from the Lithuanian and Crown Metrica, and treasury records, the composition of the family landholdings, the routes of their expansion (land grants from the monarch, purchases, and marital acquisitions), and the mechanisms of estate management are reconstructed. Particular attention is paid to the first division of the estates at the turn of the 1570s – 1580s: initially as a practice of allocating revenues and usage, and subsequently as a legally formalized agreement with clearly defined boundaries, rights, and obligations of the parties. The study refines the nomenclature of settlements and the structure of the estate complex centred on the town of Zaslav. The article includes two documentary appendices and tables that summarize information on part of the clientela (servitor-vassals) of the Princes of Zaslav and present the composition of the family’s holdings across all three districts of the Volhynian Voivodeship in the last quarter of the sixteenth century.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".