Occupational diseases in British Columbia : frequency, distribution and implications for prevention
Bibliographic record
Abstract
The main objective of this study was to assist in the prevention of occupational diseases (OD1s) in British Columbia by providing information concerning accepted wage-loss claims for OD's in B.C. To achieve this objective, data in the Workers' Compensation Board's OD Register was analyzed by extraction, classification and tabulation of accepted wage-loss claims for OD's during the period 1978-1982, by diagnosis, number of cases, rate, type of exposure, age, sex, individual year and industrial subclass. Also, a model for regular annual reporting of registered OD's in B.C. was developed. To collect and analyze the data, an updated exposure classification was developed. It was observed that OD's caused by physical factors such as ultraviolet radiation, repetitive motion, noise and friction and pressure were most common in B.C., representing 63% of the total of 19,622 OD cases during 1978-1982. Among the top ten causes of OD's are also chemical and biological agents ("cleaning compounds", "other chemicals", "other alkalies", "animals and insects", "acids" and "cement and mortar"). The OD rates per 1,000 manyears of employment were increasing during 1978-1981 and the small drop in 1982 is probably related to the economic depression in B.C. The highest OD risk industries (measured by OD incidence rate/1,000 manyears) were: "construction and repair of small vessels" (39.8), "shingle and shake mills" (37.5), and "bakeries and manufacturing of food products" (17.6). It was concluded that these results indicated clearly that preventive actions should be improved in B.C. to decrease the number of workers who annually suffer from OD's. It is suggested that occupational health services (OHS) would help to achieve this goal, through expanding and making more efficient and effective education, regulation and services concerning OD prevention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".