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Record W4224300626 · doi:10.1163/22127453-bja10012

A Ming Minister’s Advice on Controlling and Selecting Military Commanders

2022· article· en· W4224300626 on OpenAlexaff
Jun Fang

Bibliographic record

VenueJournal of Chinese Military History · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsWestern University
Fundersnot available
KeywordsChinaLawSelection (genetic algorithm)State (computer science)Political scienceCivil affairsCommand and controlCivil–military relationsEngineeringPoliticsComputer scienceTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Qiu Jun (1421–1495) was an important Ming civil official who was also a prolific author. One of his works, the Daxue yanyi bu, devotes nineteen of its 160 chapters to military affairs. Qiu Jun puts particular emphasis on the importance of choosing the right commanders. The main body of this article consists of a translation of the passages from the Daxue yanyi bu dealing with rulers’ selection and management of military commanders. Qiu Jun’s opinions on the control and selection of generals are not always practicable, yet they shed considerable light on the Chinese state’s strategies to control the military, civil-military relations, and the military examination system in imperial China.

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)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.021
GPT teacher head0.266
Teacher spread0.245 · 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
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
Published2022
Admission routes1
Has abstractyes

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