Occupational noise exposure at sea: A socio-legal study on fish harvesters’ perceptions in Newfoundland and Labrador, Canada
Bibliographic record
Abstract
Introduction: Noise is a significant health hazard for fish harvesters. Chronic exposure to hazardous noise levels of 85 dB (A) for an 8-h work shift can have adverse health impacts, including both auditory and non-auditory health problems such as noise-induced hearing loss, stress, hypertension, sleeping disorders, and impaired cognitive performance. Methods: A review of legislation and policies governing workplace noise exposure, as well as qualitative, semi-structured interviews, were conducted to assess how fish harvesters in Newfoundland and Labrador (NL) manage onboard occupational noise exposure and perceive noise-induced health problems, as well as the barriers and challenges associated with preventing and controlling noise exposure. Results: to control and prevent onboard noise by employers in Newfoundland and Labrador. Fishers reported that their workplace is noisy. Over time, fish harvesters adapted to the environment and learned to tolerate loud noise, displaying fatalistic behavior. Fish harvesters reported avoiding using hearing protection onboard due to navigation safety concerns. Fishers reported hearing loss as well as other non-auditory health problems. Inadequate noise control measures adopted by employers, a limited supply of hearing protection onboard, and a lack of regular hearing testing, training, and education were identified as the main barriers to preventing and controlling noise exposure. Conclusion: and the development of hearing conservation initiatives by employers are necessary. All stakeholders, including the federal and provincial governments, WorkplaceNL, and not-for-profit fishing organizations in the province, are strongly recommended to initiate training and education campaigns to help fish harvesters understand noise exposure and adopt preventive measures.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".