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Record W2340365094

Command Decision: Leadership Lessons from the Strategic Air War Against Germany

2016· article· en· W2340365094 on OpenAlexvenueno aff
Lee W. Lacy

Bibliographic record

VenueJournal of military and strategic studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsOffensiveStrategic bombingPolitical scienceWorld War IIManagementHistoryOperations researchLawEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

The history of strategic bombing in World War II is well-documented, but is also found in the unlikeliest of places, in a theatrical production performed in the New York theater—on Broadway— in 1947. The play, Command Decision , by William Wister Haines, is an examination of the decision making process involved with the strategic bombing campaign in the European Theater of Operations.  This paper uses Command Decision to examine real events in 1943—notably the raids on industrial targets of Regensburg, Schweinfurt and Stuttgart, where the 8th USAAF sustained punishing losses. Out this terrible episode of the war, when thousands of airmen lost their lives, the lessons of the bombing campaign’s Combined Bomber Offensive are significant. The leaders, events and decisions that influenced this intense and deadly episode of World War II remain relevant. The powerful lessons of leadership and command— mixed with human failing and the suffering of mankind, make a compelling story.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.196
GPT teacher head0.368
Teacher spread0.173 · 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
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
Published2016
Admission routes1
Has abstractyes

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