The Challenges of Switching ‘Sail-Fast-then-Wait’ to ‘Sail-Slow-and-Save’ in the Decarbonization of Voyage-chartered Bulk Shipping
Bibliographic record
Abstract
Abstract The past two years have seen an important momentum in the decarbonization of international shipping, a major single contributor to climate change. The International Maritime Organization has adopted its revised ghg Strategy which strives to bring the emissions of this industry to net zero by 2050. The decarbonization will be a gradual process via the adoption of new fuels and a set of efficiency-improving measures. This article addresses a particular efficiency-improving measure: just-in-time (jit) arrival. This practice seeks to slow ships down at sea and thereby cut their emissions when it is known that they would arrive at a port only to queue. While it sounds simple, several practical, commercial, and legal challenges have to be solved before this practice can become common, especially in the voyage-chartered bulk shipping sector. This article seeks to highlight these issues with particular regard to the due dispatch obligation, laytime and demurrage, laycan clauses, and the role of policy in encouraging jit arrivals.
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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 | 0.021 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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".