A Community of Practice for Knowledge Translation Trainees: An Innovative Approach for Learning and Collaboration
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
A growing number of researchers and trainees identify knowledge translation (KT) as their field of study or practice. Yet, KT educational and professional development opportunities and established KT networks remain relatively uncommon, making it challenging for trainees to develop the necessary skills, networks, and collaborations to optimally work in this area. The Knowledge Translation Trainee Collaborative is a trainee-initiated and trainee-led community of practice established by junior knowledge translation researchers and practitioners to: examine the diversity of knowledge translation research and practice, build networks with other knowledge translation trainees, and advance the field through knowledge generation activities. In this article, we describe how the collaborative serves as an innovative community of practice for continuing education and professional development in knowledge translation and present a logic model that provides a framework for designing an evaluation of its impact as a community of practice. The expectation is that formal and informal networking will lead to knowledge sharing and knowledge generation opportunities that improve individual members' competencies (eg, combination of skills, abilities, and knowledge) in knowledge translation research and practice and contribute to the development and advancement of the knowledge translation field.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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