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Record W4410158327 · doi:10.3167/hrrh.2025.510204

Vadia Guerre

2025· article· en· W4410158327 on OpenAlexvenueno aff
Ronald W. Braasch

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicFrench Historical and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Abstract English campaigns in France during the Hundred Years War were military operations and significant governmental undertakings. The monarchy needed to mobilize and deploy men, animals, and equipment across the Channel to wage war in France. Once assembled, the English army employed a complex administrative system to ensure its soldiers were funded and resourced, leaving records of financial expenditures. The often-cited Vadia Guerre (War Wages) represented one section of the military finances for such English campaigns. This article presents a snapshot of English efforts to wage war during King Edward III's final campaign in France, culminating in the Treaty of Brétigny in 1360. It utilizes a database to track the names, numbers, and payments of various English troops and subsidies for expenses. It then uses the categories of newly created knights and combat support personnel to highlight the challenges of employing administrative records in such research and complicate our understanding of service and military-financial compensation in the fourteenth century.

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)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.130
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0430.005

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 head0.057
GPT teacher head0.283
Teacher spread0.226 · 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
Published2025
Admission routes1
Has abstractyes

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