The 2006 Canadian Birth-Census Cohort.
Bibliographic record
Abstract
BACKGROUND: Evidence on socioeconomic and ethnocultural disparities in perinatal health in Canada tends to be limited to analyses by neighbourhood or for selected provinces. In 2010, the Canadian Institutes of Health Research awarded funding for a project on perinatal outcomes. This article describes the resulting 2006 Canadian Birth-Census Cohort Database. DATA AND METHODS: From the Canadian Live Birth, Infant Death and Stillbirth Database, 687,340 records of children born in Canada from May 16, 2004 through May 15, 2006 to mothers whose usual place of residence was Canada were selected as in-scope births. Deterministic rules were applied to link each person on the birth record-child, mother, father-to 2006 Census data.The cohort was restricted to records linked to a long-form questionnaire, and a cohort weight was developed. Cohort rates (unweighted and weighted) for five birth outcomes-preterm birth, small-for-gestational age, large-for-gestational age, stillbirth, and infant mortality-were compared with rates for all in-scope births across birth characteristics. Cohort rates for these birth outcomes were examined across selected census characteristics. RESULTS: Linkage rates were 91% for births surviving to age 1, 76% for stillbirths, and 80% for infant deaths matched to a birth registration. The cohort estimates were similar to those for all in-scope births, particularly after the cohort weight was applied. The cohort data produced plausible estimates of selected birth outcomes across maternal ethnocultural categories and levels of education. INTERPRETATION: The 2006 Canadian Birth-Census Cohort data can help inform perinatal surveillance and research in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".