Deprivation and unintentional injury hospitalization in Quebec children
Bibliographic record
Abstract
Injuries disproportionately affect children from deprived areas. This study examines the links between the material and social dimensions of deprivation and injury hospitalizations in children aged 14 years or under from 2000 to 2004. Hospitalization data are from the Quebec hospital administrative data system, whereas socio-economic characteristics of individuals were estimated based on the smallest geographic areas for which Canadian census data were disseminated. The Poisson regression model was used to calculate the relative risks of hospitalization for seven categories of unintentional injury. A total of 24 540 injury hospitalizations were examined. Hospitalization in children is associated with both dimensions of deprivation. Injuries to pedestrians and motor vehicle occupants and injuries related to burns and poisonings are clearly associated with both dimensions of deprivation. These inequalities should be considered in the development of preventive measures.
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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".