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Warfare and Military Organizations

2010· reference-entry· en· W2793090465 on OpenAlexvenueno aff
Clifford J. Rogers

Bibliographic record

VenueRenaissance and Reformation · 2010
Typereference-entry
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGunpowderArtilleryElitePoliticsRevolution in Military AffairsMilitary sciencePopulationPolitical scienceState (computer science)Period (music)LawFirepowerHistoryPolitical economySociologyAncient historyArchaeology

Abstract

fetched live from OpenAlex

Throughout the period c. 1350–1650, warfare was endemic in European society, and most rulers and members of the political elite were deeply involved with the maintenance and use of armies and navies. Wars and the development of the “military art” (tactics, strategy, and other aspects of the conduct of war) are interesting subjects for historical inquiry in their own right. But since the mid–20th century students of warfare and military organizations, reflecting broader trends in the discipline of history, have tended to focus less on the details of fighting than on the social history of those who served in the armed forces (a large and relatively well-documented population). Archival studies, drawing on voluminous administrative records, have provided masses of information about topics such as recruitment, supply, soldiers’ living conditions and social backgrounds, and structures of command and control. Since 1956 much of this work has been tied in one way or another to a grand debate about a “Military Revolution” in the Reformation period. Some see this Military Revolution as resulting from technical-tactical change (particularly the rising importance of gunpowder weapons, both handguns and artillery, and then the new style of fortifications developed to resist cannon) and leading to major political and social changes, particularly linked to the rise of the modern state structure. This is true both of broad surveys and of the extensive literature on the development of the various national armed forces of Europe within the period.

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: Other · Consensus signal: none
Teacher disagreement score0.736
Threshold uncertainty score0.843

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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