Birth outcomes by neighbourhood income and recent immigration in Toronto.
Bibliographic record
Abstract
OBJECTIVES: This article examines differences in birth outcomes by neighbourhood income and recent immigration for singleton live births in Toronto, Ontario. DATA SOURCES: The birth data were extracted from hospital discharge abstracts compiled by the Canadian Institute for Health Information. ANALYTICAL TECHNIQUES: A population-based cross-sectional study of 143,030 singleton live births to mothers residing in Toronto, Ontario from 1 April 1996 through 31 March 2001 was conducted. Neighbourhood income quintiles of births were constructed after ranking census tracts according to the proportion of their population below Statistics Canada's low-income cutoffs. Logistic regression was used to estimate odds ratios for the effects of neighbourhood income quintile and recent immigration on preterm birth, low birthweight and full-term low birthweight, adjusted for infant sex and maternal age. MAIN RESULTS: Low neighbourhood income was associated with a moderately higher risk of preterm birth, low birthweight, and full-term low birthweight. The neighbourhood income gradient was less pronounced among recent immigrants compared with longer-term residents. Recent immigration was associated with a lower risk of preterm birth, but a higher risk of low birthweight and full-term low birthweight.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".