Unintentional injury hospitalizations and socio-economic status in areas with a high percentage of First Nations identity residents.
Bibliographic record
Abstract
BACKGROUND: Few national studies of hospitalizations due to injuries among the First Nations population have been conducted. DATA AND METHODS: Based on 2004/2005 to 2009/2010 data from the Discharge Abstract Database, this study examines associations between unintentional injury hospitalizations, socio-economic status and location relative to an urban core in Dissemination Areas (DAs) with a high percentage of First Nations identity residents versus a low percentage of Aboriginal identity residents. RESULTS: Unintentional injury hospitalization rates were higher in the less affluent and the most remote DAs. When DAs with the same socio-economic status and location were compared, the risk of hospitalizations was greater in high-percentage First Nations identity DAs relative to low-percentage Aboriginal identity DAs. INTERPRETATION: Socio-economic conditions and remote location accounted for some, but not all, of the differences in unintentional injury hospitalizations between high-percentage First Nations identity and low-percentage Aboriginal identity DAs. This suggests that characteristics not measured in this analysis--such as environmental, behavioural or other factors--play an additional role in DA-level unintentional injury hospitalization risk.
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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 | 0.001 | 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".