Interprofessional learning in the trenches: Fostering collective capability
Bibliographic record
Abstract
The greatest resource for improving interprofessional learning and practice is the knowledge, wisdom, and energy of professionals who adapt to challenging situations in their everyday work. We call collective capability the ability of a group of professionals to balance two interdependent levels of organization of practice: what professionals know and what they do collectively over time. Organizing what professionals know links the relational value--caring for patients--to the knowledge value of practice. Organizing what professionals do includes human and organizational factors that facilitate collective work and learning: technical skills for care delivery, institutional support, and a complex mix of emotional, ethical and moral factors involved in social decision-making. Performance gaps can result from a lack of an integrated knowledge framework or from a disembodied knowledge that is not anchored in practice. Opportunities for continuous learning can be seized by documenting the source of the performance gap, and providing the relevant resources to establish the balance between the organization of knowledge and the organization of work.
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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.034 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".