Building a Primary Care Community of Practice: SCOPE as a Platform for Care Integration and System Transformation
Bibliographic record
Abstract
Strong primary care plays a foundational role in a high-functioning health system. Primary care is the main entry point to the healthcare system for patients, but in many health systems, the majority of primary care practices and physicians are functionally disconnected from, and not meaningfully integrated with, specialist care, hospital resources or team-based allied professionals. Here, we detail how a grassroots program in the Greater Toronto Area, known as SCOPE (Seamless Care Optimizing the Patient Experience), has worked to build and grow a community of practice among physicians who were previously "unaffiliated" to provide streamlined access to specialist care and virtual team-based resources. Notably, through purposeful engagement efforts, this community of practice has led to new patient-facing initiatives that respond to primary care needs. This improved integration of primary care with both hospital-based resources and specialty services, along with the initiation of new services that address population needs, demonstrates the value of this type of purposeful engagement to develop a primary care community of practice.
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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 | 0.021 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.021 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.046 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".