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Record W7015787878

Trial by Friendship: Anglo-American Relations, 1917-1918

2016· article· en· W7015787878 on OpenAlexaboutno aff

Bibliographic record

VenueProject Muse (Johns Hopkins University) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPower (physics)FriendshipWorld War IIMilitary strategyChinaIntervention (counseling)International relationsMilitary operations other than war
DOInot available

Abstract

fetched live from OpenAlex

During the crucial period of 1917-1918, the United States superseded Great Britain as the premier power in the world. The differing strategic perspectives of London and Washington were central to the tensions and misunderstandings that separated the two dominant powers in 1918 and determined how these two countries would interact following the Armistice. David R. Woodward traces the projection of American military power to western Europe and analyzes in depth the strategic goals of the American political and military leadership in this first comprehensive study of Anglo-American relations in the land war in Europe. Based on extensive research in British and American archives, the study focuses on Woodrow Wilson and David Lloyd George, whose relationship was poisoned by the mutual suspicion and hostility generated by their disagreements over strategy and military policy. President Wilson sought to use his country's military effort in western Europe as a tool to gain acceptance for his "new diplomacy." The British, anxious over the Turko-German threat to Asia and their worsening manpower situation, sought to utilize American military intervention for their own political/military purposes. Woodward's use of unpublished sources provides new perspectives on war leadership, and his analysis of the British-American interaction serves as a case study of the inevitable tension between national self-interest and efforts at collective security, even among nations that share many cultural and political values. For historians and anyone interested in military history and World War I, Trial by Friendship fills a gap in the study of Anglo-American relations by providing a strong, well- written study on an area of American history that has received scant attention from scholars. David R. Woodward is professor of history at Marshall University. "Woodward does an excellent job of analyzing the conflicting strategic goals of Washington and London. Strongly recommended."—Camaraderie "A sane, sober, and sensible account...required reading."—Canadian Journal of History "A skillfull blending of the political, diplomatic, military, and strategic issues that both unified and divided the allies."—Choice "Woodward provides the clearest picture yet of the international problems and strategic implications of creating a United States army in Europe."—Journal of American History "Woodward's mastery of the subject is revealed on every page as is his balanced and thorough scholarship. The book supercedes all previous works and provides a firm foundation for future inquiries."—Journal of Military History "A new, insightful study on war leadership. Highly recommended."—Library Journal "An engrossing book...solid, lucid, and enjoyable."—International History Review "An important contribution to the historical literature on World War I. Woodward's analysis is original."—American Historical Review

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0380.009
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0100.001

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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

Explore more

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