Work Health and Safety in Small Business-A Pilot Study in the Australian Construction Industry
Bibliographic record
Abstract
Work accidents impacts negatively on the physical, mental and social welfare of employees, increase cost of production, and make firms less competitive. The construction industry in Australia consists of 96% small business and has the fifth largest incident rates of serious injury of all industries. Nevertheless, recent statistics by the Australian Bureau of Statistics show noticeable improvement in safety performance within the construction industry compared to previous years.This descriptive pilot study attempts to verify small business contribution to this recent improvement. Ten owner managers are surveyed in order to examine their commitment to work health and safety using a 34 self-completion questionnaire. The findings show that small business owners in the construction industry take a positive approach toward work health and safety in their work environment.This study represents only a snapshot of the reality of small construction business commitment to work health and safety in Australia and can’t be generalised to a wider population, therefore further research with larger samples is required to confirm the findings of this study.
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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 | 0.003 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".