The New Federal Impact Assessment Act and Arctic Shipping: Opportunities for Improved Governance
Bibliographic record
Abstract
This chapter explores opportunities to improve the governance of shipping and related activities in the Canadian Arctic waters through the application of the federal Impact Assessment Act (IAA). It considers a range of activities potentially associated with shipping in the Arctic and their key associated impacts, such as vessels used in fishing and aquaculture, supply vessels for northern communities and industries, shipping related to the transportation of resources extracted in the Canadian Arctic, shipping related to energy projects, tourism related shipping, and the Arctic as a shipping route for global trade. The chapter then considers the role each of four distinct assessment processes under the IAA could make to the governance of shipping. Given the prevalence of other assessment processes in the Canadian Arctic, the chapter then considers how the IAA’s processes will interact with existing assessment processes beyond the IAA, such as those at territorial and Indigenous levels of government.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".