Increased rates of adverse outcomes for gestational diabetes and pre‐pregnancy diabetes in on‐reserve First Nations Women in Ontario, Canada
Bibliographic record
Abstract
AIMS: To compare the prevalence of diabetes in pregnancy, pregnancy care and adverse pregnancy outcomes in on-reserve First Nations women vs. non-First Nations women in Ontario, Canada. METHODS: A retrospective population-based cohort study was performed. All 487368 live singleton hospital deliveries between 1 April 2002 and 31 March 2010 were identified. Outcomes were defined by linking mothers and infants to provincial healthcare administrative databases. RESULTS: Diabetes in pregnancy was more prevalent in First Nations women (10.3 vs. 6.0%). They received less pregnancy care and had higher rates of adverse outcomes than non-First Nations women with diabetes. CONCLUSIONS: First Nations women are at a higher risk of diabetes in pregnancy and adverse outcomes. This highlights the need for increased care for pregnant First Nations women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".