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Record W7099472090

Infant mortality among First Nations versus non-First Nations in British Columbia: temporal

2015· article· en· W7099472090 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsInfant mortalityRural areaRelative riskChild mortalityPregnancyNeonatal deathCause of deathPopulationLive birth
DOInot available

Abstract

fetched live from OpenAlex

Background Increasingly more First Nations (FN) people have moved from rural to urban areas. It is unknown how disparities in infant mortality among FN versus non-FN women have changed over time in urban versus rural areas. Methods We conducted a birth cohort-based study of all 877 925 live births (56 771 FN and 821 154 non-FN) registered in British Columbia, 1981–2000. Main outcomes included rates, risk differences, and relative risks of neonatal, postneonatal, and overall infant death. Results Both neonatal and postneonatal mortality rates for FN infants showed a steady decline in rural areas but a rise-and-fall pattern in urban areas. Relative risks for overall infant death among FN versus non-FN infants declined steadily from 2.75 (95 % CI: 2.04, 3.72) to 1.87 (95 % CI: 1.24, 2.81) in rural areas from 1981–1984 to 1997–2000, but rose from 1.59 (95 % CI: 1.27, 1.99) (1981–1984) to 2.80 (2.33–3.37) (1989–92) and then fell to 1.89 (1.44–2.49) (1997–2000) in urban areas. Risk differences for neonatal death among FN versus non-FN infants declined substantially over time in rural but not urban areas. The disparities in neonatal death among FN versus non-FN were largely explained by differences in preterm birth, while the disparities in postneonatal death were not explained by observed maternal and pregnancy characteristics. Conclusions Reductions in disparities in infant mortality among FN versus non-FN women have been less substantial and consistent over time in urban versus rural areas of British Columbia, suggesting the need for greater attention to FN maternal and infant health in urban areas.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.216
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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