Multiple Maternities and Neighborhood Income
Bibliographic record
Abstract
This study aimed to examine differences in multiple maternities by neighborhood-income levels in Toronto, Canada. Hospital records were used to perform secondary analysis of 144,731 maternities resulting in single or multiple infants live-born to mothers residing in the City of Toronto 1996 to 2001. The independent variable was neighborhood income, defined as mean household neighborhoodincome quintiles. Multiple logistic regression analysis was used to compute adjusted odds ratios (AORs) and 95% confidence intervals (CIs). Differences by income levels were found in twin maternities but not in higher order maternities. Twin maternities were more likely to occur in the richest neighborhood-income quintile compared to the rest of the population (AOR: 1.25, 95% CI: 1.10-1.41), after adjustment for potential confounders. The positive association between high neighborhood income and twin maternities found in this study suggests that the richest neighborhoods select families whose characteristics pose them at increased risk of having twins. Further studies are needed to clarify the underlying mechanisms leading to socioeconomic differences in multiple births.
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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 | 0.002 |
| 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 | 0.001 | 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".