Inter-professional Collaboration as a Health Human Resources Strategy: Moving Forward with a Western Provinces Research Agenda
Bibliographic record
Abstract
The current gap in research on inter-professional collaboration and health human resources outcomes is explored by the Western Canadian Interprofessional Health Collaborative (WCIHC). In a recent research planning workshop with the four western provinces, 82 stakeholders from various sectors including health, provincial governments, research and education engaged with WCIHC to consider aligning their respective research agendas relevant to inter-professional collaboration and health human resources. Key research recommendations from a recent knowledge synthesis on inter-professional collaboration and health human resources as well as current provincial health priorities framed the discussions at the workshop. This knowledge exchange has helped to consolidate a shared current understanding of inter-professional education and practice and health workforce planning and management among the participating stakeholders. Ultimately, through a focused research program, a well-aligned approach between sectors to finding health human resources solutions will result in sustainable health systems reform.
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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 | 0.039 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".