Making Interprofessional Education Work: The Strategic Roles of the Academy
Bibliographic record
Abstract
Faculties (i.e., schools) of medicine along with their sister health discipline faculties can be important organizational vehicles to promote, cultivate, and direct interprofessional education (IPE). The authors present information they gathered in 2007 about five Canadian IPE programs to identify key factors facilitating transformational change within institutional settings toward successful IPE, including (1) how successful programs start, (2) the ways successful programs influence academia to bias toward change, and (3) the ways academia supports and perpetuates the success of programs. Initially, they examine evidence regarding key factors that facilitate IPE implementation, which include (1) common vision, values, and goal sharing, (2) opportunities for collaborative work in practice and learning, (3) professional development of faculty members, (4) individuals who are champions of IPE in practice and in organizational leadership, and (5) attention to sustainability. Subsequently, they review literature-based insights regarding barriers and challenges in IPE that must be addressed for success, including barriers and challenges (1) between professional practices, (2) between academia and the professions, and (3) between individuals and faculty members; they also discuss the social context of the participants and institutions. The authors conclude by recommending what is needed for institutions to entrench IPE into core education at three levels: micro (what individuals in the faculty can do); meso (what a faculty can promote); and macro (how academic institutions can exert its influence in the health education and practice 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.
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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.026 | 0.014 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".