Subjective assessments of safety, exposure to chemicals and use of personal protection equipment in seafaring
Bibliographic record
Abstract
BACKGROUND: Most of the scientific publications from the maritime area are studies about the mortality and morbidity, while studies about the present hazards of potentially dangerous exposures are relatively rare. AIMS: To describe the seafarers' assessments of the occupational safety on board, their exposure to chemicals and the use of personal protection equipment and to identify the areas for further risk assessment and preventive measures. METHODS: A questionnaire study was carried out in 11 countries among seafarers who attended a regular health examination. RESULTS: The total number of seafarers who participated in the study was 6461 (response rate 93.7%). The occupational safety on board was assessed to be very good or good in 82%. Multivariate analyses showed that the safety was assessed as lowest among ratings, seafarers<30 years of age, work in the engine rooms and on dry cargo ships. It was highest on crude oil tankers and supply ships. Fifty-five per cent of seafarers were exposed to chemicals. Personal protection equipment to chemicals was used 'always/almost always' in 93% of the exposed. Multivariate analysis showed that the use of personal protection was highest on deck, on the largest ships, on roll-on roll-off ships and on crude oil tankers. CONCLUSION: The occupational safety and the use of personal protective equipment was assessed to be significantly different in some strata of the population and in specific working areas and types and sizes of ships.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".