MétaCan
Menu
Back to cohort
Record W7135930581

Financial policy in times of crises until 19th century of the Bohemian Duchy

2021· dissertation· cs· W7135930581 on OpenAlexaboutno aff
Jiří NOVOTNÝ

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2021
Typedissertation
Languagecs
FieldSocial Sciences
TopicCentral European national history
Canadian institutionsnot available
Fundersnot available
KeywordsDuchyMonetary policyFiscal policyLate 19th centuryQuarter (Canadian coin)Financial policySpanish Civil War
DOInot available

Abstract

fetched live from OpenAlex

Financial policy in times of crises until the 19th century Abstract This thesis focuses on financial policy during crises of the Bohemian Duchy, Kingdom of Bohemia, and Lands of the Bohemian Crown within The Austrian Empire until the 19th century. I will compare monetary and fiscal approaches to tackle the gravest crises caused by war, instability, or a financial breakdown. Therefore, in this thesis, I will analyse selected crises that took place in the Bohemian Duchy located in the Bohemian Kingdom at the end of the 13th century. I will focus on the Hussite wars, the great calada during the Thirty Years War, Napoleonic Wars, the Seven Years War, the Revolution of 1848, and the Long Depression, which started in 1873. The used methods are mainly comparison, analysis, and analogy. Results of the research indicate that an improper financial policy caused the majority of crises. Governmental approaches to solving fiscal, monetary and taxation problems were worsening the situation. Financial policy concerning monetary, fiscal, and tax policy until the end of the 19th century was procyclical. If enlightened politicians appeared in an era of prosperity, their plans for reforms were generally dashed by war and need for new governmental expenditures. However, the government, especially during the crisis, was prone...

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicCentral European national historyFrench-language works237,207