Determinants of respirable crystalline silica exposure in construction in western Canada
Bibliographic record
Abstract
Task-based respirable crystalline silica (RCS) exposure monitoring data was collected from construction work sites across 3 Canadian provinces: Alberta, British Columbia (BC), and Manitoba. In total 373 RCS samples were obtained from 70 worksites across 44 companies. Sampling was conducted between May 2015 and August 2020. The overall geometric mean (GM) RCS exposure was 0.045 mg/m3 (geometric standard deviation, GSD = 6.8). Alberta had the highest average exposure and the highest variability with GM of 0.060 mg/m3 (GSD = 9.3), the GM in BC was 0.044 (GSD = 4.3), and in Manitoba the GM was 0.033 (GSD = 7.0). A multivariable model was built using forward stepwise linear regression modeling. Province, task type, work environment (indoor vs. outdoor), construction material, sampling duration, and engineering control use were all statistically significant predictors of exposure level in partial F-tests (P < 0.05). Overall, the model explained 42% of the RCS concentration variability. Task type contributed most to the model's explanatory power. The task type with highest average exposure levels was demolition (GM 0.30 mg/m3, GSD 0.49). Breaking (GM 0.16 mg/m3, GSD 8.4) and grinding (GM 0.081 m/m3, GSD 7.4) also had high-exposure levels. Working outdoors was associated with exposure levels 39% lower than indoors. Exposure control measures such as local exhaust ventilation and wetting were also associated with lower exposure levels. Among construction materials, Cement, sand, and stone were associated with higher RCS exposure levels relative to the reference material, concrete. The results of this study indicate that workers in western Canada remain exposed to RCS at levels that exceed the health-based American Congress for Governmental Industrial Hygienists Threshold Limit Value of 0.025 mg/m3. Although there were some differences in exposure levels between the provinces, the determinants of exposure were similar in all 3. The overall GM RCS exposure was 0.045 mg/m3 (geometric standard deviation, GSD = 6.8). Alberta had the highest average exposure and the highest variability with GM of 0.060 mg/m3 (GSD = 9.3), the GM in BC was 0.044 (GSD = 4.3), and in Manitoba the GM was 0.033 (GSD = 7.0).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".