Vladislav's Jagellonian, king of Bohemia, fiscal situation in the years 1471-1490
Bibliographic record
Abstract
Vladislaus Jagiellon's fiscal situation was problematic from the very beginnig of his reign. The royal sources of revenue were considerably limited. The most important incomes came from the crown property, the escheat of noblemen's estates, the mine regal, the mining undertaking, the royal mint, and the general tax. Initially, the young king was supported by his father, Casimir IV the king of Poland, who granted him probably less than 72 000 Hungarian florins during the years 1471-1473. The crown propety which was part of royal chamber embraced royal towns, monasteries, castles, and domains. The incomes produced by them, especially the so called special tax, were reduced considerably by pawning. This was especially true in case of the monasteries and castles whose importance for the royal chamber was negligible. Vladislaus held permanently only three castles, Karlštejn, the Prague Castle, and Krivoklát. There was about 35 royal towns in Bohemia. The towns paid in chamber the so called town census besides the special tax; despite of the pawning, this all together still was an important king Vladislaus' source of revenue. The towns and partially also the monasteries sought to redeem their own property or chamber payments pawned by the king. The Jews also belonged to the royal chamber, paying to it a special...
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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 | 0.000 | 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 | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".