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Record W2893038163

Canadian Civil-Military Relations in the Early “Command Era,” 1945-1955 Forging a Normative Prescription Through Rational Analysis

2015· article· en· W2893038163 on OpenAlexaffabout
Hugues Canuel

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsNormativeFraming (construction)PoliticsCold warContext (archaeology)Political scienceDemobilizationSpanish Civil WarEconomic historyLawTheologySociologyHistoryPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

recent postwar demobilisation.2Through the 1950s, Canada grew its armed forces from 30,000 to 120,000 regulars, fought a hot war in Korea, deployed a standing garrison to Europe under the North Atlantic Treaty Organization (n a t o ), joined the North American Air Defence (n o r a d ) umbrella, led the United Nations' first large peacekeeping mission in the wake of the Suez Crisis, all the while developing massive infrastructures on its home soil to support an unprecedented peacetime mobilisation.3This stands in sharp contrast to the "Management Era", deemed to have taken hold in 1964, sublimating the previous harmony through controversial innovations, the most well-known being Defence Minister Paul Hellyer's plan to first integrate and then unify Canada's three fighting services.4In Bland's view, the politician left his successors with "... an organization in great confusion, a military profession unsure of its values, its history, or its future, and with the old problems still firmly in place."5While an indictment of Hellyer the minister, this last statement also intimates that not all was well prior to 1964.The government of Progressive Conservative Prime Minister John Diefenbaker had fallen to the Liberals of Lester Pearson in 1963 largely as a result of its inability to resolve defence dilemmas since taking power in 1957.6Neither Pearson nor Hellyer intended for such a fate to befall them and many observers have since linked unification to problems that 1 0 4 : F o r g in g A N o r m a t iv e P r e s c r ip t io n T h r o u g h R a t io n a l A n a ly s i s 2 See, among others, George F.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.242
Teacher spread0.215 · 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.

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
Published2015
Admission routes2
Has abstractyes

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