Up a river! Interprofessional education and the Canadian healthcare professional of the future
Bibliographic record
Abstract
The benefits of an interprofessional approach to patient care are becoming well known and the adoption of these ideas for collaboration by future healthcare professionals will be influenced by positive exposures during pre-licensure education. Although much work has been done, the establishment of interprofessional education in health care programs is still in the developmental phase in many centers. But the need for such education is obvious and urgent. Once these new professionals enter into practice, they will be expected to function as members of interprofessional teams. Therefore, they should be equipped with the skills they will need to function effectively on a team. The future of the healthcare system relies on the education of tomorrow's professionals. When we finally train healthcare professionals to perform as part of a team, "paddling in harmony", we will be able to steer toward our goal of an efficient, sustainable and safe health care system. If we do not learn to work together, we will continue to go in circles.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".