Bibliographic record
Abstract
As part of a multiphase project that developed a full-scale fatigue management program for Canadian marine pilots, the present work involved an initial trial and evaluation of two fatigue management training modules: (1) Train-the-trainer fatigue management workshop (TTT workshop); and (2) Marine pilot fatigue management workshop (MPW). One TTT workshop and three MPWs were conducted. The TTT workshop involved two full days of instruction and practice. The MPWs were one-day sessions, held in Cornwall, Montreal and Quebec City, that involved six hours of instruction and participation, with additional time for two breaks and lunch. Pilots and management from the Great Lakes pilotage authority and the Laurentian pilotage authority attended the MPW sessions. The sessions were all well received and successful according to the immediate feedback obtained through questionnaires and observation. The trainer who took the TTT workshop gave an excellent rating on all questions on the TTT questionnaire and performed very well during the two MPW sessions he led. The participants responded very favourably on the MPW questionnaire and showed a keen interest in fatigue management. They asked highly relevant questions and engaged in discussions about such subjects as the feasibility of strategies, the impact of irregular hours on their health and job conditions, and the need for change to the present pilotage system. It is recommended that the training modules be adopted by other pilotages, and that all personnel in each pilotage receive the training. The training modules will require some modification for appropriate application to each pilotage.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".