CPD and KT: Models Used and Opportunities for Synergy
Bibliographic record
Abstract
The two fields of continuing professional development (CPD) and knowledge translation (KT) within the health care sector, and their related research have developed as somewhat parallel paths with limited points of overlap or intersection. This is slowly beginning to change. The purpose of this paper is to describe and compare the dominant conceptual models informing each field with the view of increasing understanding and appreciation of the two fields, how they are similar and where they differ, and the current and potential points of intersection. The models include the "knowledge-to-action'' (KTA) cycle informing KT, models informing CPD curriculum design and individual self-directed learning, and the Kirkpatrick model for evaluating educational outcomes. When compared through the perspectives of conceptual designs, processes, and outcomes, the models overlap. We also identify shared gaps in both fields (eg, the need to explore the influence of the context in which CPD and KT interventions take place) and suggest opportunities for synergies and for moving forward.
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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 | 0.042 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".