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Record W2516856071 · doi:10.1177/0840470416649732

Engagement in system redesign

2016· review· en· W2516856071 on OpenAlexaboutno aff
Bradley Anderson, Wendy Kai Hansson

Bibliographic record

VenueHealthcare Management Forum · 2016
Typereview
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careAccountabilityHealthcare systemPublic relationsReciprocalBusinessPopulationNursingPolitical scienceMedicineEnvironmental health

Abstract

fetched live from OpenAlex

For the past several years, Interior Health (IH) has worked collaboratively with Aboriginal leaders to build strong relationships and develop an environment of reciprocal accountability and knowledge exchange. All partners are committed to working together to change the healthcare system so that it responds appropriately and effectively to the needs of a population of people with the poorest health outcomes. The development of the IH Aboriginal Health and Wellness Strategy is an example of meaningful engagement with First Nations communities in the IH region at the system level. The strategy was built by IH, led by First Nations, and developed in collaboration with First Nations, Urban, and Métis partners. It aims to address the shared long-term goal of improving the overall health and wellness of Aboriginal people and enable a cultural transformation to overcome the barriers that are stopping Aboriginal people from seeking care from a shared healthcare system.

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)0.047
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.047
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.075
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.005
Science and technology studies0.0020.005
Scholarly communication0.0080.009
Open science0.0040.009
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0150.002

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 head0.228
GPT teacher head0.498
Teacher spread0.270 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations38
Published2016
Admission routes1
Has abstractyes

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