The IMO Regulatory Framework for Arctic Shipping: Risk Perspectives and Goal-Based Pathways
Bibliographic record
Abstract
The International Maritime Organization (IMO), in its capacity as a specialized agency of the United Nations, is the global regulator to ensure safety, security, environmental standards, efficiency and sustainability of international shipping. The current regulatory framework of IMO, which is developed and maintained on a continuous basis, includes over 50 international instruments and numerous codes, guidelines and circulars that cover every aspect of international shipping ranging from design, construction, equipment, manning and operation to ship recycling. The safety net of the universally adopted IMO regulations currently covers approximately 1.5 million seafarers and more than 60,000 ships. With declining ice cover leading to an increasing spiral of traffic despite the many hazards, safety of shipping in polar waters and, in particular, the Arctic and its fragile environment is a current focus area of IMO and purported to be addressed by the Organization through a set of goal-based regulatory standards. This chapter provides an overview of the IMO framework and process of shipping regulation and maps the transition from prescriptive to goal-based approach. Risk-based approaches to safety are discussed in the context of the Canadian Arctic. The chapter further reviews the IMO instruments relevant to the Arctic, including the Polar Code, and discusses the approaches to implementation at the flag state, coastal state and regional level, lending new insights and future pathways on tiered implementation of the IMO goal-based framework.
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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 | 0.029 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.023 | 0.007 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".