Canada and ‘re-engaging’ United Nations peacekeeping. A critical examination.
Bibliographic record
Abstract
With the advent of Justin Trudeau in 2015, Canada appears to be determined to revitalize its historic role as a peacekeeper. Central is whether Canada truly abandoned UN peacekeeping per se. In order to answer this question, the following needs to be addressed. The first relates to the meaning of UN peacekeeping and the evolution of peacekeeping’s aims, tools, and basic principles, such as consent, impartiality, and the appropriate use of force. The second concerns the role of Canada in UN peacekeeping from 1947 to 2017. Given the nature of UN peacekeeping and Canada’s role from 1947 to 2017, the rhetoric of Trudeau government is confusing. Canada never truly disengaged from UN peacekeeping. Rather, for a variety of reasons, it shifted from UN-led to UN-approved peace operations. If the Trudeau government’s re-engagement means he intends to support UN-led missions rather than UN-approved peace operations in contradiction from the current trend, this has several implications that require careful examination. The final chapter articulates some of these implications.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.035 | 0.032 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".