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Record W2070380523 · doi:10.12927/hcq.2014.24007

Improving Health Equity for First Nations, Inuit and Métis People: Ontario’s Aboriginal Cancer Strategy II

2014· article· en· W2070380523 on OpenAlexfundaboutno aff
Alethea Kewayosh, Loraine D. Marrett, Usman Aslam, Richard Steiner, Margaret Moy Lum-Kwong, J Imre, Abigail Amartey

Bibliographic record

VenueHealthcare Quarterly · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
FundersDivision of ChemistryCancer Care Ontario
KeywordsEquity (law)Cancer incidenceHealth equityCancerHealth careMedicineEconomic growthIncidence (geometry)GerontologyPolitical sciencePublic healthNursing

Abstract

fetched live from OpenAlex

Cancer incidence is increasing more rapidly and cancer survival is worse among Ontario's First Nations, Inuit and Métis (FNIM) populations than among other Ontarians. Cancer Care Ontario's Aboriginal Cancer Strategy II aims to reduce this health inequity and to improve the cancer journey and experience for FNIM people in Ontario. This comprehensive, multi-faceted strategy was developed and is being implemented with and for Aboriginal Peoples in Ontario in a way that honours the Aboriginal Path of Well-being.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.792

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 studies0.0010.000
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 head0.053
GPT teacher head0.398
Teacher spread0.345 · 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 designOther design
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

Citations25
Published2014
Admission routes2
Has abstractyes

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