Wicked problems in Canada's Arctic during Cold War 2.0
Bibliographic record
Abstract
Canada faces major challenges in its governance of the North given the impact of climate change and some of the challenges currently posed by Russia and China that are a departure from the rules-based order that existed for a 36-year period following the Cold War. When combined with the general world-wide challenges that both Russia and China are making in relationship to international law, including the prohibition against invading other nations, we are led to conclude that we are well into what we may rightly call Cold War 2.0. The complexities we are experiencing now in the North suggest that many of the new problems might be characterized as wicked problems because they are difficult to solve, there are no clear solutions, and different stakeholders and experts have different ideas of how to proceed. Sometimes, the resolution to the problem creates other problems. The purpose of this paper is to illustrate experts’ views of wicked problems we are more likely to experience and the challenges this presents. The paper offers suggestions for how decision-makers might seek to respond to wicked problems in the North in a new Cold War 2.0 era.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".