Discoveries and Dissimulations: The Impact of Abortion Deaths on Maternal Mortality in British Columbia*
Bibliographic record
Abstract
One of the most striking improvements in the health of Canadian women was brought about by the lowering of the risk of maternal mortality. Between the 1930s and 1960s the chances of dying in pregnancy fell from about 1 in 150 to 1 in 3,000. Maternal deaths, which in the early 1930s had accounted for 10 to 15 per cent of all deaths among women in the childbearing years, fell in three decades to 2 to 3 per cent. 1 This dramatic breakthrough was so welcomed that few have asked why it occurred so late. In the early nineteenth century about one-quarter of the deaths of women aged between 15 and 50 were related to pregnancy and its complications. With the onrush of medical improvements associated with Joseph Lister’s discovery of antisepsis in 1867 there was the real possibility of eliminating many of the traditional causes of maternal death. 2 Conditions did improve somewhat, but if one were to judge by the statistical data the gains made in the first decades of the twentieth century were still disappointingly modest. Whereas the infant mortality rate fell from 120 deaths per 1,000 live births at the beginning of the century to 68 per 1,000 by 1936, the maternal mortality rate continued to hover at about 5 per 1,000 and actually rose to a century high of 5.8 per 1,000 in 1930. 3
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".