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Record W4312544563 · doi:10.1080/02722011.2022.2113968

Comparative Analysis of Services for Canadian Inuit for Tuberculosis, Suicide Prevention, and Smoking Cessation: Common Themes and Underlying Issues

2022· article· en· W4312544563 on OpenAlexafffundabout
Marika Morris

Bibliographic record

VenueThe American Review of Canadian Studies · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsCarleton University
FundersCanadian Institutes of Health ResearchCanadian Cancer Society
KeywordsPublic healthGovernment (linguistics)TuberculosisPsychological interventionSuicide preventionEnvironmental healthPolitical scienceMental healthMedicineEconomic growthPoison controlCriminologySociologyNursingPsychiatry

Abstract

fetched live from OpenAlex

This article provides a comparative analysis of Government of Canada interventions in three areas of Inuit public health: tuberculosis (TB), suicide, and smoking. Each public health case study focuses on a different period from the 1940s to the present. Common themes across these times and health issues are identified: the extent of the health issue is more prevalent among Inuit; each problem began with colonization, particularly from the resulting trauma, family separation, cultural interruption, and removal of decision making; resources for Inuit health are insufficient; racism, language, and cultural barriers impede Inuit access to healthcare; overcrowded housing, food insecurity, and unresolved trauma play roles in each health issue in each time period. The article argues that public health initiatives for Inuit need to be designed by Inuit and adequately funded, and to address the root causes of the problems.

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)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.857

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.014
Science and technology studies0.0090.002
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.125
GPT teacher head0.468
Teacher spread0.343 · 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 designQualitative
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
Published2022
Admission routes3
Has abstractyes

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