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Record W3178735957 · doi:10.1017/s0008938921000042

Livonian Mercenary Warfare and Fiscal Responses to the Military Crisis of 1558–1561

2021· article· en· W3178735957 on OpenAlexaff
Joseph Sproule

Bibliographic record

VenueCentral European History · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval European History and Architecture
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRivalryNegotiationCompetition (biology)Political sciencePolitical economyPower (physics)EconomyLawSociologyEconomics

Abstract

fetched live from OpenAlex

Abstract Ivan the Terrible's 1558 invasion of Livonia plunged the eastern Baltic into military crisis. The ensuing conflict has most often been examined in terms of competition between the burgeoning powers that, by 1561, had occupied and partitioned the territories of the Livonian Confederation. The present study instead explores the fiscal and military responses of the Livonians themselves. An institutional approach to the dissolution of Old Livonia is eschewed in favor of one that foregrounds shifting networks of regional power holders endeavoring to defend their interests against a messy backdrop of mercenary warfare, military enterprise, factional rivalry, personal ambition, ad hoc negotiation, and desperate expediency. The Livonian experience reveals much about the struggles of small European polities and regional elites faced with the escalating financial demands of warfare in an age of emerging states.

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 score0.020
Threshold uncertainty score0.039

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 communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.202
Teacher spread0.172 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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