Hospitalization due to pneumonia among Innu, Inuit and non-Aboriginal communities, Newfoundland and Labrador, Canada
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to compare hospitalization rates due to pneumonia between Innu/Inuit communities in Labrador and non-Aboriginal communities on the Northern Peninsula of Newfoundland, Canada. METHODS: This is a comparative study using data on hospitalization due to pneumonia for the period from April 1, 1995 to March 31, 2001, for the Innu/Inuit communities in Labrador and a sample of non-Aboriginal communities on the Northern Peninsula of Newfoundland. Data were obtained from the provincial hospital database. Hospitalization rates among the study groups were compared by age, gender, and type of pneumonia. RESULTS: The hospitalization rate due to pneumonia for the Innu/Inuit communities was 11.6 compared to 3.0 per 1000 population for non-Aboriginal communities (p<0.01x10(-4)). Among the Innu/Inuit communities, infants had the highest rate of hospitalization due to pneumonia (93.4 per 1000 population), while the elderly (10.2 per 1000 population) were found to have the highest rate among the non-Aboriginal sample. Overall hospitalization rate for the Innu communities (16.9 per 1000 population) was higher than that for Inuit communities (8.4 per 1000 population) (p<0.01x10(-4)). CONCLUSIONS: Aboriginal communities, particularly the Innu communities, had higher rates of hospitalization due to pneumonia compared to the non-Aboriginal sample. Findings of this study will be used as a foundation for more specific studies in an effort to increase our understanding of pneumonia and associated risk factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".