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Record W2341954021

Jasen J. Castillo, Endurance and War: The National Sources of Military Cohesion. Stanford, CA: Stanford University Press, 2014.

2016· article· en· W2341954021 on OpenAlexaffvenue
Quentin Holbert

Bibliographic record

VenueJournal of military and strategic studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVictoryCohesion (chemistry)ChinaPoliticsPolitical scienceHistoryEconomic historyPolitical economySociologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Since the earliest thinkers of ancient Greece and China, theorists have speculated about the nature of warfare; what drives men to war, what determines victory, and what are the implications of victory or defeat? Theorists from Sun Tzu to Carl Von Clausewitz all offered theories about the conduct of warfare with changing political and technological environments. Jasen J. Castillo offers his piece, Endurance and War: The National Sources of Military Cohesion , to the millennia-long dialogue and proposes his theories on how armies stay cohesive when facing dire situations.

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)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.071
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0040.004
Scholarly communication0.0040.011
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.003

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 head0.049
GPT teacher head0.277
Teacher spread0.227 · 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
GenreReview

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
Published2016
Admission routes2
Has abstractyes

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