Recognizing Change in Post-Graduate Medical Education Using the Organizational Knowledge Creation Model
Bibliographic record
Abstract
Context: Université de Montréal medical school implemented Competency-based medical education, an important organizational change. Recognizing and reporting progress towards change is critical for success. Yet, informative frameworks that allow educators to track progress aren’t available. We used the Organizational Knowledge Creation Model for such a purpose. Purpose: This paper reports on how we used the Organizational Knowledge Creation Model to recognize change towards Competency-based Medical Education implementation. Method: Because Organizational Knowledge Creation Model focuses on the relationships between individuals and social structures, we selected an embedded case study approach. Diverse case sampling was used to select three academic departments: internal medicine, surgery and psychiatry. Data collection was conducted at two intervals, two years apart. Semi-structured interviews (individual and group) were conducted with Department Heads and Educators. Thematic analysis was conducted on the 15 interview transcripts and coded according to the four Organizational Knowledge Creation Model stages. Results: As implementation begins, selected and trained Educators critically revisit teaching routines and develop common conception of Competency-based medical education. This enables communication with wider audiences and intervene within existing working groups where Competency-based medical education is “broken down” into practical concepts. Educators’ roles evolved from “expert” who disseminates knowledge about Competency-based medical education, to responsive and pragmatic tutors who develop practical tools with peers and program directors. Conclusion: The Organizational Knowledge Creation Model framework provided a deep understanding of ongoing change. Study participants, interviewed twice, described their perception of change as it progressed as well as insights into the underlying dynamics. As medical schools evolve, Organizational Knowledge Creation Model may be a valuable conceptual tool to track progress and describe tangible changes.
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".