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Record W2406508316

Potential years of life lost at ages 25 to 74 among Status Indians, 1991 to 2001.

2011· article· en· W2406508316 on OpenAlexaffabout
Michael Tjepkema, Russell Wilkins, Jennifer Pennock, Neil Goedhuis

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsDemographyResidenceMedicineYears of potential life lostCensusGerontologySocioeconomic statusLife expectancyEnvironmental healthPopulation
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Compared with other Canadians, First Nations peoples experience a disproportionate burden of illness and disease. Potential years of life lost (PYLL) before age 75 highlights the impact of youthful or early deaths. DATA AND METHODS: The 1991 to 2001 Canadian census mortality follow-up study tracked a 15% sample of adults aged 25 or older over more than a decade. This study examined mortality among people aged 25 to 74-55,600 Status Indians (39,200 on reserve and 16,500 off reserve) and 2,475,700 non-Aboriginal adults-all of whom were enumerated by the 1991 census long-form questionnaire. Age-standardized PYLL rates were calculated, based on the number of person-years at risk before age 75. RESULTS: Status Indian adults had 2.5 times the risk of dying before age 75, compared with non-Aboriginal adults. Results did not differ greatly by residence on or off reserve. Relative and absolute inequalities were greatest for unintentional and intentional injuries. Socio-economic factors such as income, education, housing and employment explained a substantial share of the disparities in premature death. INTERPRETATION: Status Indian adults had higher rates of premature mortality. Socio-economic factors played an important role in those disparities. Injuries were important contributors to both relative and absolute inequalities.

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)0.000
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 score0.172
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.253
Teacher spread0.230 · 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

Citations28
Published2011
Admission routes2
Has abstractyes

Explore more

Same venuePubMed→Same topicIndigenous Health, Education, and Rights→French-language works237,207→