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Record W2147567012 · doi:10.1177/0022009410392408

Western Allied Intelligence and the German Military Document Section, 1945-6

2011· article· en· W2147567012 on OpenAlexaboutno aff
Derek R. Mallett

Bibliographic record

VenueJournal of Contemporary History · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsGermanSection (typography)Military intelligenceWork (physics)World War IIPrisoners of warWestern europeFirst world warLawPolitical scienceOperations researchLibrary scienceHistoryEngineeringAncient historyArchaeologyComputer scienceBusiness

Abstract

fetched live from OpenAlex

In the year following the end of the second world war in Europe, various high-ranking Wehrmacht officers agreed to work for a co-ordinated US, British, and Canadian military intelligence operation called the ‘Hill Project’. This endeavor, which eventually expanded to almost 200 German prisoners of war, conducted research and analysis of the German Military Document Section at Camp Ritchie, Maryland, and produced over 3600 pages of reports for the Western Allied governments. The Hill Project constitutes a little-known aspect of the interesting postwar relationship between the West and their former enemies. This article examines the main goals of this program and the kind of information these research projects provided to Western Allied military intelligence. It contends that during its operation at Camp Ritchie, the main body of work completed by the Hill Project studied Wehrmacht methods as a means to potentially improve the structure and procedures of the Western Allied armies. Moreover, a select group of the Hill Project prisoners later transferred to Fort Hunt, Virginia, and assisted in preparing a defense of Western Europe against a potential invasion by the Soviet Army.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.131
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0040.003
Scholarly communication0.0050.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.065
GPT teacher head0.295
Teacher spread0.229 · 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 designQualitative
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

Citations1
Published2011
Admission routes1
Has abstractyes

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Same venueJournal of Contemporary HistorySame topicIntelligence, Security, War StrategyFrench-language works237,207