Theories, relationships and interprofessionalism: Learning to weave
Bibliographic record
Abstract
In this article, we illustrate the application of a number of theoretical frameworks we have used to guide our work in interprofessional education (IPE) and collaborative interprofessional care (IPC). Although we do not claim to be experts in any one of these theories, each has offered important insights that have broadened our understanding of the complexities of interprofessional learning and practice. We have gained an appreciation for an increasing number of theories relevant to IPE and IPC, and, as a result, we have woven together more key principles from different theories to develop activities for all levels of interprofessional learners and clinicians. We pay particular attention to relational competencies, knotworking/idea dominance, targeted tension and situational awareness. We are now drawing on the arts and humanities and complexity theory to foster relationship-building learning. Evaluation of our endeavors will eventually follow these latter theories for methods that better match the human and social experiences that underpin learning. Our "theoretical toolbox" therefore may be of value to educators who develop and implement creative interprofessional learning activities, as well as clinicians interested in moving toward more effective collaboration.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 teacher head, 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".