Exploring Context and the Factors Shaping Team-Based Primary Healthcare Policies in Three Canadian Provinces: A Comparative Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper discusses findings from a high-level scan of the contextual factors and actors that influenced policies on team-based primary healthcare in three Canadian provinces: British Columbia, Alberta and Saskatchewan. The team searched diverse sources (e.g., news reports, press releases, discussion papers) for contextual information relevant to primary healthcare teams. We also conducted qualitative interviews with key health system informants from the three provinces. Data from documents and interviews were analyzed qualitatively using thematic analysis. We then wrote narrative summaries highlighting pivotal policy and local system events and the influence of actors and context. Our overall findings highlight the value of reviewing the context, relationships and power dynamics, which come together and create "policy windows" at different points in time. We observed physician-centric policy processes with some recent moves to rebalance power and be inclusive of other actors and perspectives. The context review also highlighted the significant influence of changes in political leadership and prioritization in driving policies on team-based care. While this existed in different degrees in the three provinces, the push and pull of political and professional power dynamics shaped Canadian provincial policies governing team-based care. If we are to move team-based primary healthcare forward in Canada, the provinces need to review the external factors and the complex set of relationships and trade-offs that underscore the policy process.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it