Comparative Perspectives on the Development of Canadian Arctic Shipping: Impacts of Climate Change and Globalization
Bibliographic record
Abstract
Climate change does impact sea ice, with a significant reduction of its extent and thickness. Climate change thus facilitates navigation, without making it easier, and indeed has contributed to the expansion of traffic in the Canadian Arctic, with a fivefold increase since 2000. However, there is a discrepancy between expectations that the melting of sea ice triggered and actual levels of shipping, especially regarding transit volumes. This can be accounted for by the fact that drivers of shipping in the Arctic, especially in Russian waters, are linked to the development of natural resources extraction and the perception that Arctic shipping markets may not readily fit into global strategies adopted by shipping companies. Potential economic drivers of Arctic shipping, extraction and transit, are related to the insertion of the region into globalized markets. With regard to climate change, conditions for the development of shipping in the Canadian and Russian Arctic are increasingly shaped by market, political and legal developments from outside the region, giving credence to the idea that the Arctic is increasingly inserted into the global economy. This chapter analyzes the evolution of Canadian Arctic shipping in the face of these developments.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".