Bibliographic record
Abstract
In response to Kerry Buck and Michael W. Manulak's recommendations for the future of the UN, this essay highlights two problems that Canada faces in its current UN engagement. First, diplomacy and Global Affairs Canada are underfunded. Second, Canadian leadership has failed to adequately meet the political challenges of twenty-first century multilateralism. Focusing on the second, I argue that Canada must address key political difficulties to make a meaningful difference in the future of the UN. Without a politically sound vision and policy, increased Canadian investment in the UN is insufficient. I propose three areas where Canada can shift its engagement and recommend further actions. These include: (1) Canada-US relations; (2) the UN Charter and international law; and (3) Canada's relationship with the Global South.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.010 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 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".