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Record W7065994866

Finanční situace českého krále Vladislava Jagellonského v letech 1471-1490

2008· dissertation· en· W7065994866 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2008
Typedissertation
Languageen
FieldArts and Humanities
TopicMedieval European History and Architecture
Canadian institutionsnot available
Fundersnot available
KeywordsCensusRevenuePaymentQuarter (Canadian coin)Poor relief
DOInot available

Abstract

fetched live from OpenAlex

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...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.209
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicMedieval European History and ArchitectureFrench-language works237,207