Abstract WP358: The Toronto Stroke Networks Virtual Community of Practice: Collaborative Change Leadership to create enhanced purpose for best practice implementation
Bibliographic record
Abstract
Background/Issues Systems changes within the Toronto Stroke Networks (TSNs) prompted the development of a virtual community of practice to connect administrators, academics, and clinicians, enhance professional and organizational expertise, foster implementation of best practices, and improve patient outcomes in stroke care. Purpose To use a collaborative approach to develop and implement an innovative method of supporting knowledge translation of stroke best practices, the TSNs Virtual Community of Practice (TSNs VCoP). Methods Four 90 minute focus groups were held using an appreciative inquiry methodology to identify desired outcomes of the TSNs VCoP its features, structure, and components. An iterative process, using beta testers, generated stakeholder stories, and integrating the TSNs VCoP into systems change and knowledge translation initiatives were used to inform the ongoing development of the initiative to enhance utility and knowledge exchange. Results Focus Group Results Four desired outcomes for use of the TSNs VCoP: Better knowledge exchange via peer-to-peer support Improved dissemination and adoption of stroke best practices. More efficient ways to find relevant people or material resources Collaboration between stakeholders across the TSNs Three key features of the TSNs VCoP were identified to support these desired outcomes: A searchable membership directory A resource repository Discussion forums Generative Results A fourth key feature (4. Groups Section) was identified by beta testers and key stakeholders as a need to support additional program implementation. This was built into the site to allow for public, private, or hidden communications among groups of healthcare providers working with the same interests on a particular topic. Conclusions Using a generative and collaborative approach has enhanced the utility and integration of the TSNs VCoP as a knowledge exchange tool. It has ensured a responsive and adaptive approach that supports the changing needs of its stakeholders. The themes from the focus groups reinforce the identified need and benefits of the TSNs VCoP.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".