The Canadian Armed Forces in the Arctic: Building Capabilities and Connections
Bibliographic record
Abstract
The Arctic has emerged as a topic of tremendous hype over the last decade, spawning persistent debates about whether the region’s future is likely to follow a cooperative trend or spiral into conflict. Official Canadian military statements, all of which anticipate no near-term conventional military threats to the region, predict an increase in security and safety challenges and point to the need for capabilities suited to a supporting role in an integrated, whole-of-government (WoG) framework. This entails focused efforts to enhance the government's all-domain situational awareness over the Arctic, to prepare responses to a range of unconventional security situations or incidents in the region, and to assist other government departments (OGD) in their efforts to enforce Canadian laws and regulations within national jurisdiction. Despite popular commentaries suggesting that military deficiencies in the North make Canada vulnerable, we argue that the Canadian Armed Forces are generally capable of meeting its current and short-term requirements and is responsibly preparing to meet the threats to Canadian security and safety that are likely emerge over the next decade.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".