Core competencies in the science and practice of knowledge translation: description of a Canadian strategic training initiative
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
BACKGROUND: Globally, healthcare systems are attempting to optimize quality of care. This challenge has resulted in the development of implementation science or knowledge translation (KT) and the resulting need to build capacity in both the science and practice of KT. FINDINGS: We are attempting to meet these challenges through the creation of a national training initiative in KT. We have identified core competencies in this field and have developed a series of educational courses and materials for three training streams. We report the outline for this approach and the progress to date. CONCLUSIONS: We have prepared a strategy to develop, implement, and evaluate a national training initiative to build capacity in the science and practice of KT. Ultimately through this initiative, we hope to meet the capacity demand for KT researchers and practitioners in Canada that will lead to improved care and a strengthened healthcare system.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: yes · About a Canadian topic: yes | Other design | high |
| grok | Metaresearch Domain: Incentives · Genre: Other About the Canadian research system: yes · About a Canadian topic: yes | Other design | high |
| opus | Metaresearch Domain: Incentives · Genre: Other About the Canadian research system: yes · About a Canadian topic: yes | Not applicable | medium |
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 | 0.020 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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