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Record W4405123734 · doi:10.1177/09683445241300472

‘Our Frankenstein’? Spenser Wilkinson, Strategic Planning and the Creation of the British General Staff

2024· article· en· W4405123734 on OpenAlexaff
Paul M. Ramsey

Bibliographic record

VenueWar in History · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsCentre for Social InnovationUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsStrategic planningManagementHistoryOperations managementSociologyEngineeringEconomics

Abstract

fetched live from OpenAlex

Victorian Britain lacked an expert department for strategic planning. Spenser Wilkinson, Britain's leading thinker about war, advocated the creation of a general staff. This article examines how Wilkinson transmitted the essence of the German General Staff into English and popularised the concept of a ‘strategic brain’ for the Army. Many politicians wanted a British staff limited to studying ‘theories’ of war. Wilkinson argued a functioning staff worked on the ‘practicalities’ of strategic planning for possible future wars. Wilkinson's ideas played a great part in the creation of the British General Staff, shaping British strategy for the First World War.

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)0.001
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 score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.034
GPT teacher head0.274
Teacher spread0.240 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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