A comparison of perinatal and infant mortality rates in British Columbia and Finland: Similarities and differences
Bibliographic record
Abstract
Introduction: Despite similarities, perinatal and infant mortality rates between British Columbia, (BC) Canada and Finland differ. Key variables that may influence stillbirth, early neonatal, perinatal and infant mortality rates in BC and Finland were studied. Methods: After standardizing definitions, data for all births between 2001 and 2009 from provincial and national registries were used to compare perinatal outcomes between BC and Finland. Annual change was evaluated with regression analyses. Results: Births before 22 weeks gestation were excluded. All mortality rates per 1000 were lower in Finland vs BC (perinatal: 5.1 vs 6.2, stillbirth: 3.4 vs 3.9, early neonatal 1.7 vs 2.4, infant 2.9 vs 4.0; all p Higher multiple birth and preterm birth rates in BC are affecting mortality rates. Finland’s policy of single embryo transfer is a potential explanation. It is possible to have good perinatal outcomes and low caesarean section rates. Conclusions: The Finnish health care system may suggest possible solutions for improved perinatal outcomes. Lower per capita health care expenditures in Finland do not appear to have adversely affected perinatal outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".