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Record W1941634070 · doi:10.21971/p7ww23

A Reevaluation of the Impact of the Hundred Years War On The Rural Economy and Society of England

2008· article· en· W1941634070 on OpenAlexvenueno aff
Brad Wuetherick

Bibliographic record

VenueCrossing boundaries · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipSpanish Civil WarNew englandRural societyRural economyEconomyPolitical scienceDevelopment economicsPolitical economyEconomicsRural areaEconomic growthLaw

Abstract

fetched live from OpenAlex

Most scholars have argued that the Hundred Years War negatively impacted the economy and society of England. They have focused primarily on four aspects of the war: the burden of taxation on the English populace, the effects of purveyance on rural society, the effect of recruitment on the labour force of England and the costs of supporting military expeditions. However, in each case the actual degree of impact can be called into question or offset by appealing to other scholarship, or by drawing attention to related positive benefits that are too often overlooked. Beyond this, one must also consider the benefits of war in the form of new industry and the influx of money from high wages, rewards, ransoms, and the spoils of war. This paper seeks to examine both the positive and negative impacts of the Hundred Years War on the rural society and economy of England and to demonstrate that the overall impact of the war was not as negative as the majority of historians have previously maintained.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.247
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 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

Citations1
Published2008
Admission routes1
Has abstractyes

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