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Record W6987257800

Shelf life extended: the longevity and continued relevance of the binational North American Aerospace Defense Command

2016· dissertation· en· W6987257800 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicMilitary and Defense Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRelevance (law)MultitudeNavyAerospaceSoviet unionMaritime security
DOInot available

Abstract

fetched live from OpenAlex

This thesis asks why the North American Aerospace Defense Command (NORAD) continues to exist and remain relevant in the defence of North America following the disappearance of the threat of the Soviet Union at the end of the Cold War. This thesis argues that NORAD’s binational nature is key to understanding the command’s continued role in continental defence. By employing the international relation theories of functionalism and neoliberal institutionalism as a lens of analysis to understand binational defence cooperation, NORAD’s origins as a binational defence command tasked with the air defence of North America, and its acquisition of its responsibilities for drug interdiction, the continental interior, and for maritime warning are analyzed. NORAD’s longevity and continued relevance can be attributed to the command’s binational nature, which has allowed the command to focus on and institutionalize specific functional-technical solutions to select issues of mutual concern in continental defence and security for Canada and the U.S.

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)0.003
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: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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
Published2016
Admission routes1
Has abstractyes

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