A Circumpolar Perspective on Northern Development: Is Canada Falling Behind?
Bibliographic record
Abstract
Advance Online Article posted January 2024. Page numbers not yet final.This essay considers the state of the contemporary Circumpolar World and provides a general overview of the way the various circumpolar jurisdictions are addressing the challenges and opportunities of the twenty-first century. It considers how northern areas are attracting the resources necessary to lessen the socio-economic divide between northern and southern/urban areas. An overview of infrastructure, basic services, economic development, regional leadership, security, Indigenous governance, and plans for the future of the countries and regions that make up the Circumpolar North reveals significant strengths and challenges. This examination focuses, in particular, on where Canada sits in comparison to its northern neighbours, a perspective that does not always put Canada in the best light. In many respects, Canada’s efforts in the North lag—sometimes considerably—behind circumpolar norms (aside from Russia). National and sub-national governments in Canada have not always attracted the funding, commitment, and vision needed to capitalize on the political, technological, and economic resources needed to better serve the peoples of the North; in recent years, some Arctic regions have done much better than others.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".