Bibliographic record
Abstract
This basic qualitative study explored how educationalists in Canadian medical schools established and enacted their pedagogic leadership in curriculum change. Two research questions were formulated to accomplish this purpose: 1) how do educationalists establish their pedagogic leadership in Canadian medical schools for curriculum change, and 2) how do educationalists enact pedagogic leadership in medical schools during curriculum change? Data included eight semi-structured, in-depth interviews with educationalists from four medical schools in Canada. Data also included document analysis. Data analysis used procedures from constructivist grounded theory: constant comparison, memos, theoretical sensitivity, and initial and focused coding. Participants represented a range of demographics: medical school, years in position, gender, graduate degrees, and leadership position. Findings show that to establish pedagogic leadership, participants needed to gain access to the community, learn its rules, and accumulate sufficient capital. Once established, participants chose how to enact it. Choices were influenced by personal motivations, organizational climate, and risks associated with enacting leadership. When enacting leadership, participants led curriculum change directly and formally, in ways visible to others (choosing to speak loudly). They also enacted pedagogic leadership that was informal, indirect, and often invisible (choosing to speak softly). Regardless of choice, participants used a responsive approach that was collaborative and flexible. From these findings, three conclusions were drawn. First, to establish pedagogic leadership in medical schools, educationalists must accumulate sufficient capital. Second, before enacting leadership, educationalists evaluate their options for enacting leadership in change. Third, educationalists provide pedagogic leadership to catalyze curriculum change. However, in that process, they must remain responsive to the context in which they act.--Author's abstract
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".