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Record W2620265519

The Canadian Armed Forces and the Institutional Challenges of 1960–1970

2013· article· en· W2620265519 on OpenAlexaboutno aff
Éric Ouellet, Devin Conley

Bibliographic record

VenueGuerres mondiales et conflits contemporains · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsPeacekeepingExcellenceUnificationReputationPolitical scienceChristian ministryOrder (exchange)Public administrationMilitary justicePolitical economyLawSociologyEconomicsFinance
DOInot available

Abstract

fetched live from OpenAlex

The 1960s and 1970s have often been described as the golden age of peacekeeping operations for the Canadian Forces. From Cyprus to Haiti to Congo, the Canadian Forces have earned a reputation for excellence during their peacekeeping missions. However, these years were also marked by institutional turmoil, which has mostly gone unnoticed outside the Canadian defense world. Two major institutional innovations, namely the unification of the armed forces into a single command structure during the 1960s, and the creation of a national headquarters within the administrative structure of the Ministry of Defense in the early 1970s, had a significant impact on the Canadian Forces and this impact is still being felt today. This article proposes to examine these profound changes in the Canadian Forces in the light of institutional analysis in order to highlight institutional dynamics specific to the defense of Canada, namely the oscillation between efficiency and effectiveness.

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)0.004
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.352
Threshold uncertainty score0.752

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.008
Science and technology studies0.0230.030
Scholarly communication0.0120.003
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.048
GPT teacher head0.284
Teacher spread0.236 · 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
Published2013
Admission routes1
Has abstractyes

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