Rethinking Canada’s engagement in Southeast Asia: lessons from the Canada-ASEAN Centre
Bibliographic record
Abstract
One objective of Canada’s Indo-Pacific Strategy is to strengthen people to-people ties between Canada and the members states of the Association of Southeast Asian Nations (ASEAN). The Singapore-based Canada-ASEAN Centre, founded in 1989, shared a similar objective during its years of operation. This article revisits the experience of the Canada-ASEAN Centre to highlight lessons relevant for Canada’s renewed engagement in Southeast Asia. These include being attuned to local needs and nurturing sustainable networks between individuals and institutions. Expanding academic exchanges and collaboration in science and technology can deepen Canadian understanding of Southeast Asia, foster innovation, and help tackle global challenges. The Centre’s experience also illustrates the value of entrepreneurial prospecting to identify areas for collaboration, as well as securing long-term financial support and maintaining focus on strategic interests during political transitions. Equally important are careful coordination among stakeholders and a clear-eyed assessment of the competition in Southeast Asia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".