Comparison of On-Reserve Road Versus Off-Reserve Road Motor Vehicle Crashes in Saskatchewan, Canada
Bibliographic record
Abstract
BACKGROUND: There is an overwhelmingly high incidence of severe injuries caused by motor vehicle crashes (MVCs) among Aboriginal Canadians as compared with the general population. METHODS: The authors obtained MVC data for a 3-year period, 2003-2005, from Saskatchewan Government Insurance (SGI) for collisions occurring on on-reserve roads (n = 1270) together with a randomly selected sample of MVCs from off-reserve roads (n = 1270) in Saskatchewan. They compared the collision characteristics using bivariate and multiple logistic regressions. RESULTS: On-reserve MVCs were more likely to include multiple collisions and result in severe injuries than the off-reserve sample. A number of factors were significantly related to the increased risk of on-reserve collisions as compared with the reference group for each variable. INTERPRETATION: Factors from all 3 levels (human, environmental, and vehicle factors) are associated with on-reserve MVCs.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".