The compensation experience of hand-arm vibration syndrome in British Columbia
Bibliographic record
Abstract
BACKGROUND: Hand-arm vibration syndrome (HAVS) is a relatively common occupational disease, especially in certain industrial sectors. Affected workers in many jurisdictions are eligible for compensation, but little is known about the behaviour and characteristics of workers seeking compensation for HAVS. AIMS: To characterize the workers seeking compensation for HAVS based on demographics, occupation and disease characteristics. METHODS: All accepted claims for HAVS from 1999 to 2008 in British Columbia were reviewed. RESULTS: The average claimant was 50 years old and had worked 25 years. The average latency period for developing HAVS symptoms was 18 years, and half the number of symptomatic workers waited 5 years or more before filing a claim. Loggers developed symptoms, on average, after 17 years of exposure, significantly earlier than mechanics, who developed symptoms after 24 years of work. Loggers waited longer than mechanics to file claims, with a median delay of 6 years, compared with 3 years for mechanics. The majority of HAVS claims involved severer vascular and sensorineural symptoms. CONCLUSIONS: Claimants commonly delay filing compensation claims and this may result in severer symptoms when the claims are filed. Further study is required to explain this delay.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".