NORAD’S maritime warning mission: why the only new mission? the limits of functionalism
Bibliographic record
Abstract
This thesis asks why was only a maritime warning mission added to the binational North American Aerospace Defense Command’s (NORAD) existing aerospace warning and control mandate and not other missions? There were other viable options that could have come from the fallout of 9/11 to improve security and defence of North America such as maritime surveillance, maritime control, not to mention land and the cyberspace domains. In the end, NORAD was assigned only maritime warning in 2006. Using the international relation theory of functionalism as a framework to understand Canada-US defence policy decisions and joint defence initiatives, the maritime warning mission addition can be partially explained but it is not sufficient. By investigating from the Cold War era when NORAD was established until the post 9/11 era when the command was eventually signed in perpetuity, this thesis argues that functionalism alone is insufficient. It is not just a functional logic and the need for specific functional-technical solutions that underscores the origins and continued existence of NORAD as a binational organization but also the unique nature of the Canadian brand of functionalism where the Canadian military, in reality, takes the lead in shaping security decisions that favour and prioritize US decisions. This investigation concludes maritime warning was adopted by NORAD because it was the least controversial and was acceptable to Canadian and US military “professionals” in NORAD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".