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Record W3011401232 · doi:10.12927/hcpol.2020.26132

Health Policy as a Barrier to First Nations Peoples’ Access to Cancer Screening

2020· article· en· W3011401232 on OpenAlexaffvenueabout
Joshua Tobias, Jill Tinmouth, Laura C. Senese, Naana Afua Jumah, Diego Llovet, Alethea Kewayosh, Linda Rabeneck, Mark Dobrow

Bibliographic record

VenueHealthcare policy · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsNOSM UniversityPublic Health OntarioOntario Institute for Cancer ResearchSunnybrook Health Science CentreCancer Care Ontario
Fundersnot available
KeywordsContext (archaeology)Cervical cancerCancer screeningCervical cancer screeningColorectal cancerPolitical scienceMedicineBreast cancerColorectal cancer screeningHealth policyCancerEconomic growthFamily medicineEnvironmental healthPublic healthGeographyNursingInternal medicineEconomicsColonoscopy

Abstract

fetched live from OpenAlex

BACKGROUND: First Nations peoples in Ontario are facing increasing rates of cancer and have been found to have poorer survival. Cancer screening is an important strategy to improve cancer outcomes; yet, Indigenous people in Canada are less likely to participate in screening. Ontario has established organized breast, cervical and colorectal cancer screening programs; this paper examines the health policy context that informs these programs for First Nations peoples in the province. METHOD: This paper follows an embedded multiple-case study design, drawing upon a document review to outline the existing policy context and on key informant interviews to explore the aforementioned context from the perspective of stakeholders. RESULTS: Policies created by agencies operating across federal, regional and provincial levels impact First Nations peoples' access to screening. Interviews identified issues of jurisdictional ambiguity, appropriateness of program design for First Nations persons and lack of cultural competency as barriers to participation in screening. CONCLUSION: Federal, provincial and regional policy makers must work in collaboration with First Nations peoples to overcome barriers to cancer screening created and sustained by existing policies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0140.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.062
GPT teacher head0.452
Teacher spread0.390 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations13
Published2020
Admission routes3
Has abstractyes

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