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Record W2099060810 · doi:10.1093/ije/dyt147

Data Resource Profile: 1991 Canadian Census Cohort

2013· article· en· W2099060810 on OpenAlexaffabout
Paul A. Peters, M.K.G. Tjepkema, Ruth C. Wilkins, Philippe Finès, Dan L. Crouse, Phil C.W. Chan, Richard T. Burnett

Bibliographic record

VenueInternational Journal of Epidemiology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsStatistics CanadaHealth CanadaUniversity of New Brunswick
Fundersnot available
KeywordsCensusCohortSocioeconomic statusDemographyPopulationRecord linkageEducational attainmentCohort studyMedicineEthnic groupGerontologyGeographyEnvironmental healthEconomic growthSociology

Abstract

fetched live from OpenAlex

The 1991 Canadian Census Cohort is the largest population-based cohort in Canada (N=2,734,835). Prior to the creation of this Cohort, no national population-based Canadian cohort was available to examine mortality by socioeconomic indicators. The 1991 Canadian Census Cohort was created via the linkage of a sub-sample of respondents from the mandatory 1991 Canadian Census long-form to historical tax summary files, Canadian Mortality Database, Canadian Cancer Database, 1991 Health and Activity Limitation Survey and a sub-sample of the Longitudinal Worker File. Overall ascertainment of mortality and cancer is anticipated to be nearly complete and the Cohort is broadly representative of most groups in the Canadian population. The Cohort has been used to examine mortality outcomes by different indicators of socioeconomic status, occupational categories, ethnic groups, educational attainment, and for exposure to ambient air pollution. Results have shown that the estimated remaining years of life at age 25 differed substantially by income adequacy quintile, educational attainment, housing type and Aboriginal ancestry.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.079
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.026
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0790.030

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 head0.138
GPT teacher head0.442
Teacher spread0.303 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations45
Published2013
Admission routes2
Has abstractyes

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