Canada's Health Human Resource Challenges: What is the Fate of Our Healthcare Heroes?
Bibliographic record
Abstract
Each year, the Canadian health education system graduates thousands of health professionals who have the best intentions of practising to their full scope of knowledge and skills to help improve the patient care experience in this country. However, a recent research study points to the fact that members of the healthcare team may be practising in a challenging environment in which only a limited number of their skills are actually being used. The Michener Institute for Applied Health Sciences believes that these issues, which include increased role specialization, limited scopes of practice, rapidly advancing technology, and challenges transitioning from hospital to community settings, have broader health education and health system implications that need to be addressed by policy makers, educators, and healthcare system leaders in order to enhance health professional education as well as patient care.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.039 | 0.021 |
| Scholarly communication | 0.025 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".