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Record W4238371948 · doi:10.22215/etd/2017-12187

Canada's Defence Policies, 1987-1993: NATO, Operational Viability, and the Good Ally

2017· dissertation· en· W4238371948 on OpenAlexaffabout
Ian Weatherall

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsCarleton University
Fundersnot available
KeywordsAllianceWhite paperGovernment (linguistics)Task forceCold warPolitical sciencePublic administrationWhite (mutation)Foreign policyNational securityLawOperations researchEngineeringPolitics

Abstract

fetched live from OpenAlex

This thesis uses documents from the Department of Defence and the Department of External Affairs to analyze the 1987 White Paper on Defence and the changes in defence priorities in the period 1987-1993. The purpose of the White Paper was to improve the functionality of Canada’s military, offer a full commitment to NATO, and portray Canada as a good ally. The end of the Cold War in 1989-1991 and a deep recession from 1989-1992 forced the government to reduce the military budget, and the White Paper policies never reached fruition. Canada’s NATO allies valued Canada’s forces in Europe, and the government was initially willing to fund a Task Force in Europe. The decision in 1992 to cancel the Task Force and focus on the core capabilities of the military damaged Canada-NATO relations, but Canada continued to be a contributing member of the alliance and a player in European security.

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)0.007
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 score0.261
Threshold uncertainty score0.857

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0150.006
Scholarly communication0.0110.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.288
Teacher spread0.277 · 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
Published2017
Admission routes2
Has abstractyes

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