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Record W2885343915 · doi:10.1093/gerhis/ghy073

The Sinews of Habsburg Power: Lower Austria in a Fiscal-Military State 1650–1820

2018· article· en· W2885343915 on OpenAlexaff
Joseph F. Patrouch

Bibliographic record

VenueGerman History · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEuropean Political History Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsState (computer science)Economic historyMonarchyPower (physics)Spanish Civil WarPolitical sciencePeriod (music)HistoryLawPoliticsArt

Abstract

fetched live from OpenAlex

William B. Godsey, a historian affiliated with the Institute for Modern and Contemporary Historical Research of the Austrian Academy of Sciences, has produced a detailed, archival source-based study of the Estates of Lower Austria in the period between the end of the Thirty Years’ War and the end of the Napoleonic Wars. Utilizing records from a dozen public and private archives in Austria, the Czech Republic and Slovenia (and in particular the Lower Austrian State Archive in St. Pölten, Austria), he argues for the continued importance of the Estates throughout the period, particularly in relation to financing the ever-increasing costs of the ever-enlarging army the Habsburgs enlisted to pursue their foreign policy aims and defend their hereditary holdings. In so doing, Godsey uses the justly famous Austrian source-based historical research method to overturn a couple of established truths: that the Estates represented a counter-balance to the state or crown, and that they became increasingly less significant as the centuries in question passed. To the contrary, Godsey contrasts the continued importance of the Lower Austrian Estates for financial purposes with their infamously unsuccessful French counterparts, arguing that far from being relegated to the sidelines, the Estates’ continued importance helps to explain how the Habsburgs managed to weather repeated crises and invasions, emerging ever stronger. As he writes, ‘The monarchy exhibited at all events remarkable resiliency’ (p. 360). Godsey attributes this resiliency in large part to its ability to cooperate with the local landed elites and benefit from their access to credit.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations13
Published2018
Admission routes1
Has abstractyes

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