Filing for Workers’ Compensation among Ontario Cases of Mesothelioma
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: For many types of cancer, disease attribution to occupational exposures is difficult. Mesothelioma, however, is a 'sentinel' occupational cancer associated with asbestos exposure. The present study linked workers' compensation claims data with cancer registry data to explore the completeness of reporting of mesothelioma to the Ontario Workplace Safety and Insurance Board (WSIB) according to characteristics of cases diagnosed among Ontario residents. METHODS: Two data sources were linked at the person level: the WSIB Occupational Disease Information and Surveillance System and the Ontario Cancer Registry. Filing rates were calculated as the proportion of Ontario Cancer Registry mesothelioma cases (International Classification of Diseases - Oncology code 905) that linked to a WSIB-filed cancer claim. Filing rates were calculated for the period 1980 to 2002, and trends were calculated by year, age and county of residence at diagnosis. RESULTS: The filing rate for compensation has increased little over the past 20 years, reaching a high of 43% in 2000. Overall, filing rates were highest among pleural mesothelioma cases among men (range 27% to 57%). Filing rates were highest among individuals 50 to 59 years of age and declined substantially throughout the retirement years. There was substantial variation in filing rates by area of residence, with the highest rate being in Lambton County, Ontario. CONCLUSION: The filing rate for compensation in Ontario was much lower than the estimated proportion of cases eligible for compensation. The increased filing rate in Lambton County was likely related to this community's awareness of the association between asbestos and mesothelioma. Physicians can play an important role in educating patients of their potential entitlement to compensation benefits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".