Creating a sustainable model for stroke system change
Bibliographic record
Abstract
Purpose The purpose of this paper is to develop an infrastructure and leadership capacity for a sustainable approach to collaborative change in a complex health-care system. Design/methodology/approach An infrastructure for system change and a mechanism to build capacity for change leadership was developed. This involved (1) using a community of a practice model to create a change community, (2) developing an iterative engagement and change process and (3) integrating collaborative change leadership skills and knowledge development within the process. Change leadership was evaluated using Wenger's phases of value creation. Findings A change community of 62 members across 19 organizations codeveloped a change process that aligns with Cooperrider's 4D Cycle. The change community demonstrated application of change leadership learnings throughout the change process. Originality/value A tailored approach was required to support sustainable transformational change in the Toronto stroke system. This novel methodology provides a framework for broader application to systems change in other complex systems that support both local and system-wide ownership of the work.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".