Farm‐related fatal injury of young and older adults in Australia, 1989–1992
Bibliographic record
Abstract
This paper describes the types of, and circumstances surrounding, unintentional farm-related fatal injuries involving young and older adults in Australia. Information was obtained from an inspection of coronial files for the period 1989-1992. Around 14% of all farm-related fatalities in Australia during 1989-1992 were of young adults aged 15-24 years and approximately one-quarter were of older adults aged > or = 55 years. Young adults were commonly fatally injured in motor vehicle incidents and in incidents involving firearms. Tractors were the most common agent involved in fatal incidents involving older adults. Intervention measures to prevent fatalities of older adults in agriculture should focus on the safe use of tractors, while for young adults it appears prevention efforts should centre around safe use of firearms and operation of motor vehicles on the farm. Ways to overcome barriers to the use of injury prevention measures in rural Australia should be further explored.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".