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Record W1501544996

Cancer-related health behaviors and health service use among Inuit and other residents of Canada’s north

2009· article· en· W1501544996 on OpenAlexaboutno aff
James Ted McDonald, Ryan Trenholm

Bibliographic record

VenueSocial and Economic Dimensions of an Aging Population Research Papers · 2009
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsResidenceMedicinePsychological interventionEnvironmental healthLogistic regressionIncidence (geometry)Binge drinkingObesityCommunity healthDemographyGerontologyCancer screeningPublic healthCancerNursingSuicide preventionPoison control
DOInot available

Abstract

fetched live from OpenAlex

Objective – To identify the extent to which differences between Inuit and other residents of Canada’s North in a set of health behaviors and health service use related to cancer incidence and diagnosis can be accounted for by demographic, socio-economic and geographic factors. Study Design – Data on residents aged 21-65 who live in Canada’s North are drawn from the 2000-01 and 2004-05 Canadian Community Health Surveys and the 2001 Aboriginal People’s Survey. Methods – Multivariate Logistic regression analysis is applied to 1) a set of health behaviors including smoking, binge drinking and obesity, and 2) a set of basic health service use measures including consultations with a physician and with any medical professional, Pap smear testing and mammography. Results – Higher smoking and binge drinking rates and lower rates of female cancer screening among Inuit are not accounted for by differences in demographic characteristics, education, location of residence or distance from a hospital. Conclusions – Factors specific to Inuit individuals and communities may be contributing to negative health behaviors associated with increased cancer risk, and to a lower incidence of diagnostic cancer screening. Policy interventions to address these issues may need to be targeted specifically to Inuit Canadians.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.098
GPT teacher head0.437
Teacher spread0.339 · 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.

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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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