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The Indigenous primary health care and policy research network: Guiding innovation within primary health care with Indigenous peoples in Alberta

2021· article· en· W3129516323 on OpenAlexafffundabout
Lynden Crowshoe, Anika Sehgal, Stephanie Montesanti, Cheryl Barnabé, Andrea Kennedy, Adam Murry, Pamela Roach, Michael Green, Cara Bablitz, Esther Tailfeathers, Rita Henderson

Bibliographic record

VenueHealth Policy · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsQueen's UniversityMount Royal UniversityUniversity of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsIndigenousCommissionHealth careHealth policyEquity (law)Political sciencePublic administrationHealth equityPublic relationsNursingMedicineLaw

Abstract

fetched live from OpenAlex

In 2015, the Truth and Reconciliation Commission of Canada released its Final Report with 94 Calls to Action, several of which called upon the health care sector to reform based on the principles of reconciliation. In the province of Alberta, Canada, numerous initiatives have arisen to address the health legacy Calls to Action, yet there is no formal mechanism to connect them all. As such, these initiatives have resulted in limited improvements overall. Recognizing the need for clear leadership, responsibility, and dedicated funding, stakeholders from across Alberta were convened in the Spring of 2019 for two full-day roundtable meetings to provide direction for a proposed Canadian Institutes of Health Research Network Environment for Indigenous Health Research that focused on primary health care and policy research. The findings from these roundtable meetings were synthesized and integrated into the foundational principles of the Indigenous Primary Health Care and Policy Research (IPHCPR) Network. The IPHCPR Network has envisioned a renewed and transformed primary health care system to achieve Indigenous health equity, aligned with principles and health legacy Calls to Action advocated by the Truth and Reconciliation Commission of Canada.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.007
Science and technology studies0.0360.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.410
Teacher spread0.366 · 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 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

Citations26
Published2021
Admission routes3
Has abstractyes

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