Comparison of stillbirth rates by cause among Haitians and non‐Haitians in Canada
Bibliographic record
Abstract
OBJECTIVE: To compare rates of stillbirth among Haitians and non-Haitians in Canada. METHODS: A retrospective cohort study was performed using data on all stillborn and live-born singletons weighing at least 500 g in the province of Quebec, Canada, from 1981 to 2010. Stillbirth rates were computed, and hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for Haitians relative to non-Haitians. The main outcome measure was stillbirth by cause of death. RESULTS: Data for 9657 stillbirths (124 Haitian) and 2 414 751 live births (17 165 Haitian) were included. Stillbirth rates were higher for Haitians than non-Haitians (7.17 [95% CI 5.91-8.43] vs 3.96 [95% CI 3.88-4.04] per 1000 births), particularly for cord prolapse (adjusted HR 1.87, 95% CI 1.10-3.18) and placental abruption (adjusted HR 2.84, 95% CI 1.95-4.15). Haitians had higher risks of stillbirth due to cord prolapse and abruption at every week of pregnancy. Risks were not elevated for stillbirth due to congenital anomaly, a cause less responsive to urgent intervention. CONCLUSION: Stillbirth rates among Haitians are disproportionately high in Canada, particularly fetal death due to cord prolapse and placental abruption. The potential to reduce stillbirth rates through optimal emergency care in vulnerable minorities requires further investigation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.001 | 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".