Community-based research: a catalyst for transforming primary health care rhetoric into practice
Bibliographic record
Abstract
The Canadian health care system is under increased pressure to reform. While some advocates lobby for more physicians and more resources to fix the ailing system, many reports point to another potential solution – implementing primary health care (PHC). Implementing PHC will not be easy. Even though there is substantial evidence to support the efficacy and cost effectiveness of PHC, its implementation will require substantial changes in practice. Community-based research (CBR) has the potential to be the catalyst for the type of change that is required. A multidisciplinary, multisectoral inquiry team has been funded to use CBR to reconceptualize and transform PHC service delivery in British Columbia, Canada. Although the research project is in its initial phase, it is anticipated that the research will provide new, holistic, and comprehensive frameworks for practice. This paper describes the process used to bring about these changes.
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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 | 0.244 | 0.189 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.029 | 0.127 |
| Scholarly communication | 0.034 | 0.019 |
| Open science | 0.005 | 0.031 |
| Research integrity | 0.017 | 0.022 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".