Inequality in Fetal Autopsy in Canada
Bibliographic record
Abstract
PURPOSE: Inequality in use of fetal autopsy is poorly understood, despite the importance of autopsy in establishing the cause of stillbirth for future prevention. We examined fetal autopsy rates between linguistic minorities in Quebec, Canada, and assessed trends over three decades. METHODS: Using registry data on 11,992 stillbirths from 1981-2011, we calculated fetal autopsy rates for Francophones, Anglophones, and Allophones by decade. RESULTS: We found lower fetal autopsy rates for Allophones (54.4%) than Francophones (68.5%) and Anglophones (63.4%), but rates decreased over time for all language groups. After 2000, Allophones had 25% higher risk of non-autopsy relative to Francophones, with 8.8 fewer autopsies for every 100 stillbirths. Allophones who were not autopsied had 32% higher risk of having an undetermined cause of death. CONCLUSION: Inequality in use of fetal autopsy may be widespread for minorities in Canada. Efforts to decrease stillbirth in minorities may require policies to increase autopsy rates.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".