Bibliographic record
Abstract
Framing a Canadian Strategy in the Asia-PacificIn 2019, Canadian prime minister Justin Trudeau stood beside Japanese prime minister Shinzo Abe in Ottawa and called for greater Canadian-Japanese cooperation in the "Indo-Pacific."Hailed in the Canadian media at the time as a sign of Canadian middle-power diplomacy, Trudeau's comments left many in government and academic circles scratching their heads.Had Canada adopted an Indo-Pacific strategy toward Asia?Was the prime minister speaking off the cuffperhaps inadvertently using Japan's preferred nomenclature around the Asian region's strategic environment -or was he purposefully and tactically aligning Canada's strategic posture in Asia with the Abe government's Free and Open Indo-Pacific (FOIP) vision?Did he understand that in adopting an Indo-Pacific framework for Canada's foreign policy approach to Asia he was positioning his country to be a part of a controversial US-led strategy that many Asian states viewed as anti-Chinese in spirit and practice? 1 For some, such considerations were inconsequential.Canada should of course align its Asia-directed foreign and security policies with the United States and Japan -indeed, with any Western nation that shares Canada's values with respect to the international rule of law and a liberal "rules-based order." 2 At the time of Trudeau's comments, Canada was, after all, in the midst of a confrontation with the People's Republic of China (PRC) over Canada's decision to detain Meng Wanzhou,
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.374 | 0.108 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".