Geographic Inequalities of Respiratory Health Services Utilization during Childhood in Edmonton and Calgary, Canada: A Tale of Two Cities
Bibliographic record
Abstract
Young children are susceptible to respiratory diseases. Inequalities exist across socioeconomic groups for paediatric respiratory health services utilization in Alberta. However, the geographic distribution of those inequalities has not been fully explored. The aim of this study was to identify geographic inequalities in respiratory health services utilization in early childhood in Calgary and Edmonton, two major urban centres in Western Canada. We conducted a geographic analysis of data from a retrospective cohort of all singleton live births occurred between 2005 and 2010. We aggregated at area-level the total number of episodes of respiratory care (hospitalizations and emergency department visits) that occurred during the first five years of life for bronchiolitis, pneumonia, lower/upper respiratory tract infections, influenza, and asthma-wheezing. We used spatial filters to identify geographic inequalities in the prevalence of acute paediatric respiratory health services utilization in Calgary and Edmonton. The average health gap between areas with the highest and the lowest prevalence of respiratory health services utilization was 1.5-fold in Calgary and 1.4-fold in Edmonton. Geographic inequalities were not completely explained by the spatial distribution of socioeconomic status, suggesting that other unmeasured factors at the neighbourhood level may explain local variability in the use of acute respiratory health services in early childhood.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".