Climate Change and Arctic Shipping Futures: Community Perspectives on the State of Shipping and Emergency Preparedness in Canada’s Northwest Passage
Bibliographic record
Abstract
Shipping trends in the Canadian Arctic are projected to continue along a rising trajectory due to a warming climate, loss in sea ice extent, and growing economic interests in the region. This is resulting in global interest in the region and potential for Arctic shipping routes, notably the Northwest Passage (NWP). As Arctic shipping traffic continues to rapidly grow in Canada, questions arise about the preparedness of both coastal communities and government in the event of a shipping accident, or a worst-case scenario shipping disaster. This thesis aims to integrate the perspectives of residents from Pond Inlet, Nunavut, a coastal community that sits along the entranceway/exit of the NWP and is at-risk of experiencing a shipping accident in the region. A review of literature and relevant grey literature (i.e. acts, agreements, reports) was undertaken to ground the study in current research and policy. A survey with a quantitative and qualitative approach was implemented to document the perspectives of Pond Inlet residents, verifying and identifying changes in shipping patterns in the region and exploring shipping futures around the community. This also entailed acquiring an understanding of how residents perceived shipping accidents, worst-case scenarios, and emergency preparedness for their community and the region. This study contributes to current understandings and research on the state of Arctic shipping and emergency preparedness from the perspectives of coastal communities in the region.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.029 | 0.012 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".