Twisting the Lion's Tail: Collaborative Health Policy Making in British Columbia
Bibliographic record
Abstract
The respective roles of government, academia and health authorities in supporting health systems and service delivery research in the context of health policy making have often been unclear. A new strategy is necessary, one that encompasses the interdependence of research and practice and respects different kinds of knowledge and the needs and capacity of all stakeholders. Reform efforts to date have focused mainly on structural change and genuine collaboration has been pushed to the back seat. A major challenge in the health policy making process is expressing not just what we think but how we think, which requires us to be self-aware and critically reflective on how we make sense of our day-to-day realities. Using an analogy with philosophical roots, this essay explores health services research in the context of the BC health system and examines how such research and related activities can be contextualized, understood and applied in health policy making.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.034 | 0.019 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".