The BC Educator Pathway Collaborative Framework: Creating the Foundation for Nursing Education Capacity
Bibliographic record
Abstract
This paper describes the conceptual structure and organizational framework of the Educator Pathway Project (EPP), which is a unique collaborative capacity-building project creating infrastructure for integrating nursing practice learning and development throughout the service and education sectors in British Columbia. Since 2005, two major health authorities, two universities and the provincial nurses' bargaining association have been engaged in an intensive and dynamic partnership to conceptualize and fundamentally change intersectoral directions and possibilities. This unique initiative has required considerable investment and commitment among all partner organizations, resulting in a clear, shared vision of systemwide support of nursing. With the EPP now in its final year of funding, we are beginning to document its elements and interpret its significant impact on nurses and their workplaces across the regions. In this paper, we describe the overall program design, explain the collaborative partnership mechanisms through which we have been implementing the project and articulate a range of processes through which we are working together to enact significant system-level adjustments aimed at a genuine practice-education continuum. As part of sustaining a strong nursing workforce, we believe that nursing practice and education leaders across Canada are ready to employ this kind of creative approach towards realizing our common goals.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".