Creating a Culture for Interdisciplinary Collaborative Professional Practice
Bibliographic record
Abstract
The future of the health system is dependent on health professionals re-tooling the way we practice together. No longer can a multi-disciplinary model support the complex health needs of many clients nor can any one-health profession have all the knowledge needed to provide total patient-centred care. However, our current education and health systems are structured around a multidisciplinary model of practice with physicians or nurse practitioners as decision-makers and rarely are clients included in care planning. True interdisciplinary practice is defined as a partnership between a team of health professionals and a client in a participatory, collaborative and coordinated approach to shared decision-making around health issues, requires a revamping of how future health professionals are educated and how the system can accommodate shared decision-making. A client-centered collaborative professional practice model is proposed in this paper as a means for fostering and facilitating the culture for this change.
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 | 0.079 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.055 |
| Scholarly communication | 0.030 | 0.017 |
| Open science | 0.004 | 0.035 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".