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Record W960780908 · doi:10.11575/prism/26177

Fighting as Colony? 1st Canadian Corps in Italy, 1943-1945

2013· dissertation· en· W960780908 on OpenAlexaboutno aff
Christine E. Leppard

Bibliographic record

VenuePRISM (University of Calgary) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsAeronauticsEngineering

Abstract

fetched live from OpenAlex

In the summer of 1943, Canadian Minister of National Defence J.L. Ralston and Chief of Staff Lieutenant-General Ken Stuart pressured the reluctant British Chiefs of Staff to send 1st Canadian Corps to the Italian Campaign. This decision was not popular with all of Canada’s top brass. Army Commander General Andrew McNaughton argued that fighting in Italy was not in Canada’s best interest. He urged Ralston to visit Washington and insist on taking part in strategy sessions of the Combined Chiefs of Staff. Then the Canadians could decide their best course of action with an eye on strategy. Ralston replied that he could not do so. Canada was fighting as a junior partner in a coalition war, and had adopted a position of “contribution without representation.” This dissertation assesses the implications of the Canadian government’s disconnection from Allied strategy-making for 1st Canadian Corps in the Italian Campaign. It also examines whether Canada’s national interest— which, second to the defeat of Nazi Germany, was defined as waging a recognisable, independent war effort without imposing conscription—was advanced when fighting within the coalition of nations in Italy from 1943-1945, as manifested in the Anglo-Canadian relationship. It argues that the Canadians made decisions about 1st Canadian Corps and the Italian Campaign without ever having a clear picture of Anglo-American strategic objectives for the theatre, caused by serious problems of Allied communication for which both the British and Canadians were complicit. This led to tension and resentment in the Anglo-Canadian alliance, which had knock-on effects on the operational level. The Canadians eventually realised that their interests could only be protected by considering strategy, but it came too late for the situation to be meaningfully remedied.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.121
Threshold uncertainty score0.877

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0330.008
Scholarly communication0.0070.001
Open science0.0010.003
Research integrity0.0020.004
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

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