The Indigenous primary health care and policy research network: Guiding innovation within primary health care with Indigenous peoples in Alberta
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.014 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".