Estimating the financial benefits of employers’ occupational health and safety expenditures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While employer expenditures on occupational health and safety (OHS) in high income countries can be substantial, the financial benefits of these expenditures are not well described. The objective of this study is to apply a transparent methodology to estimate the financial return to employers from OHS expenditures in the Canadian province of Ontario . There were three phases in the study workplan: establishing an accurate estimate of the average direct cost of disabling work injury or illness; identifying employers in the construction, transportation and manufacturing sectors with a low incidence of work-related injury and illness; and the application of a set of plausible assumptions to estimate the financial benefits of OHS expenditures in this sample of employers with strong OHS performance. Financial benefits combined estimates of the tangible financial benefits arising from averted disabling work-related injury and illness and intangible financial benefits associated with improved employee retention and morale, improved production quality and strengthened corporate reputation. Applying these plausible assumptions, the average return on OHS expenditures was 1.24 for 289 manufacturing employers, 2.14 for 56 transportation employers and 1.34 for 88 construction employers. There was variation around these average return on investment values; 138 employers (32% of the sample) had an estimated return on investment less than 1.0, and 295 employers (68% of the sample) had a return on investment estimate greater than 1.0. The estimates of average financial return among large Ontario employers in three important economic sectors , while moderate, are positive, in the range of 1.24 to 2.14. These estimates are consistent with the range of estimates available from research in this field over the past decade.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it