Northern and Arctic Security and Sovereignty: Challenges and Opportunities for a Northern Corridor
Bibliographic record
Abstract
Key Messages Key issues related to Canada’s security and defence agenda, which involve critical and essential infrastructure development, must be considered in the development and implementation of a Canadian Northern Corridor (CNC). Canada’s northern and Arctic security and defence agenda is related to several key policy domains that are relevant from a CNC perspective. These include infrastructure development, climate change, Indigenous sovereignty and natural resource development. A CNC will gain international attention and be internationally recognized as a strategy for Canada to assert its sovereignty over its Arctic territory, including the internationally disputed Northwest Passage. The CNC advocates for the inclusion and participation of Indigenous communities. Thus, Indigenous Peoples will also carry a significant role in the monitoring and surveillance of accessibility within and to the North, improved through enhanced infrastructure development. Canada’s investments in Arctic defence infrastructure are modest comparedto those of its Russian and American neighbours. A CNC, potentially adding strategically important infrastructure in the Canadian North, will directly tie into the discourse of Arctic security and power relations. In addition to natural disasters, the Canadian North is at significant risk of human-made disasters that pose serious prospective challenges for northerners and for federal and territorial governments. The CNC will likely foster the development of surveillance and monitoring assets. The CNC rights-of-way could trigger security concerns regarding the impactof foreign investment as a security threat, especially if natural resource development is coupled with the development of strategic transportation hubs, such as ports along the coast of the Arctic Ocean. CNC transportation infrastructure would also become a part of Canada’s defence strategy as it forms a potential key asset in the defence and safeguarding of Canada’s northern and Arctic regions. Future research should identify the role of dual-use infrastructure (infrastructure that satisfies both military and civilian purposes) in the CNC context and also examine to what extent security and defence stakeholders should be involved in the CNC’s planning and implementation.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.017 |
| Scholarly communication | 0.022 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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.
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".