A discussion on the implementation of the Polar Code and the STCW Convention’s training requirements for ice navigation in polar waters
Bibliographic record
Abstract
Abstract In 2017, the International Maritime Organization (IMO) implemented theInternational Code for Ships Operating in Polar Waters(Polar Code), with mandatory requirements covering the Arctic and Antarctic Oceans. In this conjunction, theInternational Convention on Standards of Training, Certification and Watchkeeping(STCW) were amended in 2018. New training requirements were made applicable for dedicated personnel in charge of a navigational watch on ships with a Polar Ship Certificate (PSC) operating in polar waters. In association with the new training requirements amending the STCW Convention, the IMO, and Transport Canada (flag state authority) signed a Memorandum of Understanding in 2017, for Canada to develop and deliver four regional capacity-building “train-the-trainer” workshops. The objectives of these events were to assist maritime education and training (MET) institutes in enhancing the skills and competence of instructors, to develop competence-based STCW training programs, for dedicated personnel on ships operating in polar waters. This paper examines the first workshop conducted in Canada (2019), to understand the mechanisms in the interaction taking place between the IMO and the Canadian workshop developers and instructors, using the System Theoretic Accident Model and Processes (STAMP). Individual expert interviews are performed, with the main contributors directly involved in developing and conducting the workshop, to evaluate the event’s contribution to improving and specifying the STCW Convention’s training requirements, as referenced in the Polar Code, for seafarers operating in polar waters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.044 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.016 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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".