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Record W1975377995 · doi:10.1177/0020702015575916

The NORAD conundrum: Canada, missile defence, and military space

2015· article· en· W1975377995 on OpenAlexaffabout
James Fergusson

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDemiseMissile defensePolitical scienceMissileSpace (punctuation)LawPublic administrationHistoryComputer science

Abstract

fetched live from OpenAlex

Concerns about the future of the North American Aerospace Defense Command (NORAD) have forever dominated Canadian policy considerations regarding participation in the US missile defence program. Yet, fears that a Canadian decision not to participate could lead to the “demise” or marginalization of NORAD appear entirely unfounded in the wake of the formal Canadian refusal in 2005. This article identifies the reasons behind these fears relative to the nature and future of NORAD, and explains why they are both understandable and misplaced. Since the United States neither has, nor has ever had, a significant system requirement for Canadian participation, Washington has separated missile defence from the NORAD question. While this change in approach and legitimate concerns about NORAD’s marginalization have been managed through a Canadian military space contribution, it is likely that missile defence and military space cooperation will be managed on a bilateral basis largely outside of, and in support of, existing NORAD missions. This process reflects the reality of Canada–US North American defence cooperation, and NORAD’s limited place within it.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.125
Threshold uncertainty score0.906

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0110.007
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.000

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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

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