IPEC’s core competency 2 roles and responsibilities: What more do we need to implement these?
Bibliographic record
Abstract
The Interprofessional Education Collaborative (IPEC) has published guidelines to promote interprofessional collaboration. These guidelines are encompassed in four core competency sets. The core competencies are: Core 1: Value/Ethics, Core 2: Roles and Responsibilities, Core 3: Interprofessional Communication and Core 4: Teams and Teamwork. IPEC has outlined sub-competencies for each, which can be interpreted as a compilation of principles, behaviors, precepts and competencies. Together they serve to promote direction for interprofessional collaboration amongst health care professionals. However, the compilation may need more explanation to guide education and practice. Though the sub-competencies described in each core overlap in their application, specifically, Core 2: Roles and Responsibilities is explored for its underpinnings. The literature to date reflects educational delivery modes, but specific content is sparse, and not in the totality of the representative sub-competencies. Much of the literature omits the background that creates the context, and the content for, our deeper understanding of the principles. Therefore, important information is missing that underpins the competency statement set to teach and to learn these sub-competencies. The aim was to identify principles and applicable content to both support learning and to address barriers to learning, which may be essential to implement the sub-competency statements. The sub-competencies independent of further elucidation are unlikely to yield the comprehension needed for implementation and discernible actions that prompt interprofessional collaborative success.
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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 | 0.054 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".