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Record W2409404593

Birth outcomes by neighbourhood income and recent immigration in Toronto.

2007· article· en· W2409404593 on OpenAlexaffabout
Marcelo L. Urquía, John Frank, Richard H. Glazier, Rahim Moineddin

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of TorontoToronto Public Health
Fundersnot available
KeywordsNeighbourhood (mathematics)DemographySingletonOddsImmigrationPopulationLogistic regressionMedicineOdds ratioLow birth weightPlace of birthGeographyPregnancySociology
DOInot available

Abstract

fetched live from OpenAlex

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.297
Teacher spread0.281 · 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 designObservational
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

Citations79
Published2007
Admission routes2
Has abstractyes

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