Hospitalizations for unintentional injuries among Canadian adults in areas with a high percentage of Aboriginal-identity residents
Bibliographic record
Abstract
INTRODUCTION: Injuries are a leading cause of death and morbidity. While individual Aboriginal identifiers are not routinely available on national administrative databases, this study examines unintentional injury hospitalization, by cause, in areas with a high percentage of Aboriginal-identity residents. METHODS: Age-standardized hospitalization rates (ASHRs) and rate ratios were calculated based on 2004/2005-2009/2010 data from the Discharge Abstract Database. RESULTS: Falls were the most frequent cause of injury. For both sexes, ASHRs were highest in high-percentage First Nations-identity areas; high-percentage Métis-identity areas presented the highest overall ASHR among men aged 20-29 years, and high-percentage Inuit-identity areas presented the lowest ASHRs among men of all age groups. Some causes, such as falls, presented a high ASHR but a rate ratio similar to that for all causes combined; other causes, such as firearm injuries among men in high-percentage First Nations-identity areas, presented a relatively low ASHR but a high rate ratio. Residents of high-percentage Aboriginal-identity areas have a higher ASHR for hospitalization for injuries than residents of low-percentage Aboriginal-identity areas. CONCLUSION: Residents of high-percentage Aboriginal-identity areas also live in areas of lower socio-economic conditions, suggesting that the causes for rate differences among areas require further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".