A conceptual model for interprofessional education: The international classification of functioning, disability and health (ICF)
Bibliographic record
Abstract
A shared language and conceptual framework is essential to successful interprofessional collaboration. The World Health Organization's International Classification of Functioning, Disability and Health (ICF) provides a shared language and conceptual framework that transcends traditional disciplinary boundaries. This paper will familiarize readers with the ICF and describe the biopsychosocial perspective that is adopted in its conceptual framework and language. The presentation of a case study will illustrate how the ICF can enhance interprofessional learning by promoting a multidimensional perspective of an individual's health concerns. The case study will also highlight the value of the shared language and conceptual framework of the ICF for interprofessional collaboration. It is argued that a strong foundation in the principles exemplified by the ICF may serve to enhance interprofessional communication, and in so doing, encourage involvement in interprofessional collaboration and healthcare.
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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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".