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Record W2089572601 · doi:10.3402/ijch.v71i0.19752

Design and methods of the Adult Inuit Health Survey 2007–2008

2012· article· en· W2089572601 on OpenAlexafffundabout
Helga Saudny, Donna Leggee, Grace M. Egeland

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMcGill UniversitySte. Anne's Hospital
FundersCanadian Institutes of Health Research
KeywordsBaseline (sea)GeographyPublic healthHomelandEnvironmental healthSurvey data collectionSocioeconomicsMedicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The Canadian International Polar Year (IPY) program made it possible to undertake much needed health research in 3 jurisdictions within the Canadian Inuit Nunangat (homeland) over a 2-year period: Inuvialuit Settlement Region (ISR), Nunavut Territory, and Nunatsiavut. DESIGN: The Adult Inuit Health Survey (IHS) was a cross-sectional survey and provides baseline data upon which future comparisons can be made for prospectively assessing factors leading to the progression of chronic diseases among Canadian Inuit. With the help of the Canadian Coast Guard Ship Amundsen, which was equipped with research and laboratory facilities, 33 coastal communities were visited; land survey teams visited 3 inland communities. RESULTS: The Adult IHS succeeded in obtaining important baseline information concerning the health status and living conditions of 2,595 adults living in ISR, Nunavut and Nunatsiavut. CONCLUSION: Information from this survey will be useful for future comparisons and the opportunity to link with the International Inuit Cohort, a follow-up evaluation, and for the development of future health policies and public health interventions.

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)0.015
metaresearch head score (Gemma)0.001
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 score0.269
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.091
GPT teacher head0.483
Teacher spread0.391 · 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

Citations53
Published2012
Admission routes3
Has abstractyes

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