Fatal farm injuries to Canadian children
Bibliographic record
Abstract
Children on Canadian farms are at high risk for fatal injury. Ongoing surveillance of these deaths is required to affirm recurrent patterns of injury, and to determine whether historical approaches to prevention have resulted in declines in the occurrence of these traumatic events. We analyzed epidemiological patterns and trends in the occurrence of fatal pediatric farm injuries over 23 years. Records of deaths were obtained from the Canadian Agricultural Injury Reporting system. To contrast more recent data with injury patterns described historically, cases were compared between two time periods. An intentional consensus process was used to finalize key patterns and their clinical or social importance. 374 fatal farm injuries to children in Canada were identified over the 23 years of study; 253 in period 1 and 121 in period 2. While machinery and non-machinery causes of death varied between the two study periods, mean annual rates of fatal injury (approximately 4 per 100,000 children) remained similar. Notably emergent types of injury in recent years included those caused by all-terrain vehicles, skid steer loaders, and drownings. Observed declines in the numbers of fatal farm injuries are most likely attributable to analogous declines in the number of registered farms in Canada. Our findings call into question the effectiveness of pediatric farm safety initiatives that primarily focus on education. Second, while CAIR fatality data are maintained, surveillance of hospitalized injuries has been disbanded and the fatality records require updating. Only by doing so will such surveillance findings provide comprehensive information to inform prevention.
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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) | 0.001 | 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 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".