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Record W2104935739 · doi:10.22605/rrh2424

Mortality among children and youth in high-percentage First Nations identity areas, 2000-2002 and 2005-2007

2013· article· en· W2104935739 on OpenAlexafffundabout
Paul A. Peters, Lisa Oliver, Dafna Kohen

Bibliographic record

VenueRural and Remote Health · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsStatistics Canada
FundersAboriginal Affairs and Northern Development CanadaHealth Canada
KeywordsDemographyPopulationGeographyIdentity (music)Mortality rateMedicineSociology

Abstract

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INTRODUCTION: Many First Nations children live in communities that face diverse social and health challenges compared with their non-Aboriginal peers, including some of the most socio-economically challenging situations in Canada. These differences can be seen in broad indicators of the social determinants of health. Studies of mortality in Aboriginal populations across Canada are often restricted by the lack of Aboriginal identifiers on national death records. While some studies have utilised a record-linkage approach, this is often not possible for the entire country or for recent data. Some researchers have adopted a geographic approach and examined mortality and morbidity in areas that have a high percentage of Aboriginal identity residents, and have uniformly reported elevated rates of mortality and morbidity compared with other areas. The purpose of this article was to examine child and youth mortality (aged 1 to 19 years) in areas where a high percentage of the population identified as First Nations in comparison with areas where there is a low percentage of Aboriginal identity residents. METHODS: =140 779). Mortality rates were then calculated for high-percentage First Nations identity areas and compared with low-percentage Aboriginal identity areas, excluding high-percentage Métis or Inuit identity areas. Deaths were aggregated for the 3 years surrounding the 2001 and 2006 census periods, and a total of 473 deaths were recorded for 2000-2002 and 493 deaths for 2005-2007. Analysis was facilitated via the correspondence of six-digit residential postal codes on vital statistics records to census geographical areas using automated geo-coding software (Statistics Canada; PCCF+). RESULTS: Age-standardized mortality rates for children and youth in high-percentage First Nations identity areas were significantly higher than in low-percentage Aboriginal identity areas. The rate ratio for all-cause mortality for boys was 3.2 (CI: 2.9-3.6) for 2005-2007 and 3.6 (CI: 3.2-4.2) for girls. Mortality rates for injuries had the largest difference, with rate ratios of 4.7 (CI: 4.0-5.5) and 5.3 (CI:4.5-6.3) for boys in 2000-2002 and 2005-2007 and 5.5 (CI: 4.4-6.8) and 8.3 (CI: 6.8-10.1) for girls in the same period. CONCLUSION: A strength of this study is that it is the first to use national-level vital statistics registration data across two time periods to report mortality by cause for children and youth living in high-percentage First Nations areas. Vital events were geographically coded to high-percentage First Nations identity areas and compared with low-percentage Aboriginal identity areas at the Dissemination Areas level. This area-based methodology allows for mortality to be calculated for children and youth by sex and by detailed cause of death for multiple time periods. The results provide key evidence for the persistent differences in the causes of death for children and youth living in high-percentage First Nations identity 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.766
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.282
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2013
Admission routes3
Has abstractyes

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