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Record W2099133645 · doi:10.33137/rr.v30i4.11525

War and Government in the French Provinces. Picardy 1470-1560

2009· article· en· W2099133645 on OpenAlexvenueno aff
David Potter, Michel De Waele

Bibliographic record

VenueRenaissance and Reformation · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicReformation and Early Modern Christianity
Canadian institutionsnot available
Fundersnot available
KeywordsNobilityAllegianceFrontierSpanish Civil WarPoliticsNegotiationEconomic historyHistoryGovernment (linguistics)Service (business)Index (typography)Political scienceAncient historyLawEconomyEconomics

Abstract

fetched live from OpenAlex

70 / Renaissance and Reformation / Renaissance et Réforme becomes rather obtrusive.Certainly more recent scholarship on the experience and social make-up of seventeenth-century Mennonites is much less negative.This point leads us to the one major drawback of van Deursen's important study, one that is likely not his fault.Why did it take ten years to see the work appear in English translation?Van Deursen's excellent and balanced analysis of Dutch society deserves to have had an international audience much sooner.Research conducted by Dutch scholars on popular religion, culture and witchcraft, for example, has virtually exploded in the last decade.As a result, some of Plain Lives* conclusions seem outdated by the fascinating findings published since 1981.On the whole, however, van Deursen*s study deserves to be read by all those interested in understanding the world that was early modem Netherlands.Written in a highly readable and engaging fashion, marvellously blending anecdotal and scientific evidence, Plain Lives provides a solid evidentiary basis for arguing that the experience of early modem Dutch people diverged considerably from that of their contemporaries elsewhere.Students of European social history will find it a well-documented study proving that the experience of common people in that period was not uniformly bleak.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.645
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.213
Teacher spread0.197 · 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.

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

Citations9
Published2009
Admission routes1
Has abstractyes

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