MétaCan
Menu
Back to cohort
Record W4407578251 · doi:10.4337/9781035326570.00033

Driven by technology: the rise and protracted decline of US–Canada North American defense organization

2025· book-chapter· en· W4407578251 on OpenAlexaboutno aff
Joseph T. Jockel, Joël J. Sokolsky

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

United States–Canada defense cooperation has been driven by successive military technological advances in strategic nuclear air and naval forces and conventional threats. This mutually beneficial cooperation peaked at the height of the Cold War in the late 1950s and early sixties following the establishment of the binational North American Aerospace Defense Command (NORAD) in 1958. There would be no overarching bilateral defense organizations. Indeed, during the subsequent decades, the integration of United States strategic defense collaboration in the face of threats experienced an uneven yet decidedly diminished evolution, notwithstanding the continued existence of external threats to the continent. Not even the establishment by Washington of the United States Northern Command (USNORTHCOM) in 2003 and the creation by Ottawa of Canada Command in 2006 to meet the post-9/11 terrorist challenges to homeland security and defense would halt the decline in formal institutional bilateral, continental defense integration. Both governments took unilateral measures to ensure the protection of their homelands from a new external threat. From a military-technological standpoint, the strategic defensive value of Canadian air and maritime space to the United States has progressively declined. This, along with America's underlying preference to preserve a core independent military posture and Canadian sovereignty sensitivities, has meant that while the defense of the continent against external threats has been a close and friendly bilateral undertaking, it has been one that has been accompanied by an ever-declining need for organizational military integration.

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)0.003
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.192
Threshold uncertainty score0.937

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0220.011
Scholarly communication0.0120.004
Open science0.0020.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0170.002

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEdward Elgar Publishing eBooksSame topicCanadian Policy and GovernanceFrench-language works237,207