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Moving beyond the historical quagmire of measuring infant mortality for the First Nations population in Canada

2014· article· en· W2015703631 on OpenAlexafffundabout
Brenda Elias

Bibliographic record

VenueSocial Science & Medicine · 2014
Typearticle
Languageen
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchUniversity of New South Wales
KeywordsIndigenousInfant mortalityCognitive reframingPopulationDisadvantagedEconomic growthPoliticsMedicineDemographyPolitical scienceEnvironmental healthSociologyLawEconomicsPsychology

Abstract

fetched live from OpenAlex

Infant mortality is a metric influenced by societal, political and medical advances. The way vital events are collected and reported are not always uniform. A lack of uniformity has disadvantaged some groups in society. In Canada, a multi-jurisdictional vital statistics system has truncated our ability to produce infant mortality rates for the Indigenous population. To understand how this evolved, this paper outlines the history of infant mortality, generally and internationally, and then documents the efforts to harmonize the collection and reporting of vital statistics (births and deaths) in Canada. Following this analysis is a historical review of vital event reporting for Canada's Indigenous population. A major finding of this paper is that racism, reframing, and jurisdictional posturing has limited our ability to accurately estimate live births and infant deaths for the Indigenous population. To improve Indigenous infant mortality estimation, Canada's governments need to transcend multijurisdictional challenges and fulfill international reporting obligations to Indigenous communities.

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)0.007
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.624

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.010
Science and technology studies0.0050.003
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0010.002
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 head0.083
GPT teacher head0.408
Teacher spread0.325 · 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 designTheoretical or conceptual
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

Citations10
Published2014
Admission routes3
Has abstractyes

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