Bibliographic record
Abstract
Canada, despite its geographical location in North America, following its closest allies, mainly the USA, seeks to strengthen its influence in the Indo-Pacific region. The Canadian Government sees significant opportunities for the development of its economic, diplomatic and military potential. Canada’s Indo-Pacific Strategy, announced in 2022, has become the doctrinal basis of this policy, systematizing it in three key areas – economic, military and humanitarian. The article examines the issue of the transformation of the terminology base used, the regional Strategy of Canada as a mid-ranking power in the Indo-Pacific region, the main directions of its policy, and analyzes its doctrinal design with regard to the presence of goals, objectives, risks and threats in the Strategy. The author also focuses on the “anti-Chinese” aspect of the Strategy as a combination of diplomatic, economic and military means of the Canadian “containment” policy toward the Communist Party of China, whose growing influence, according to the Canadian political circles and the expert community, carries risks for regional stability and security, for a regional order based on rules and regulations. The study shows that in the long term, the priorities of Canada’s Strategy in the Indo-Pacific are updating the system of bilateral economic, diplomatic and defense agreements, as well as supporting the defense potential of partner countries. At the same time, despite the desire to strengthen its military presence in the region, the expansion of economic and trade development with regional actors will remain a key aspect of Canada’s policy.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".