Occupational health and safety management systems - a review of practices in enterprises in Botswana
Bibliographic record
Abstract
Unsafe working conditions create heavy burdens in workplaces and on the wellbeing of workers. Despite this, \nOccupational Health and Safety Management Systems (OHSMS) to reduce accidents and diseases in workplaces \nremain inadequate in many countries, including Botswana. An exploratory cross-sectional study, using \nsecondary data, was undertaken to establish OHSMS practices in various industrial sectors in Botswana. The \nresults showed that a quarter (27.6%) and about half of small and medium enterprises (SMEs), respectively, and \njust over half (60%) of large enterprises, have existing OHSMS. Only 29.2% of enterprises had an OHS policy \nstatement. The elements of OHSMS were not uniformly implemented across all enterprises, with SMEs faring \npoorly. However, 71.1% of enterprises reported provision of induction courses. OHSMS is not widely practiced \nin Botswana, raising concerns for worker wellbeing, particularly in SMEs. Further research is needed to identify \ngaps and the development of a coherent OHSMS for the country.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 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".