Facilitators and barriers for the recruitment and retention of family physician anaesthesiologists in Canada: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Family physician anaesthesiologists (FPAs) are essential to providing surgical, critical and obstetrical care in rural communities of Canada. They experience pressing challenges like burnout, isolation and limited opportunities for professional growth. There is a lack of studies synthesising the available evidence on the factors associated with recruitment and retention of FPAs in Canada. We aim to systematically review and describe the nature of the scientific evidence on the facilitators and barriers to the recruitment and retention of FPAs in Canada, and to identify areas to inform potential solutions. METHODS AND ANALYSIS: Our scoping review will search Pubmed, Embase (Ovid), Scopus and grey literature for empirical or theoretical publications in English or French on facilitators and barriers to the recruitment and retention of FPAs in Canada. We will conduct a narrative synthesis of the included publications. ETHICS AND DISSEMINATION: Our results will guide future research and initiatives to enhance the availability of FPAs in Canadian rural and remote settings. The results will be shared through professional networks, presentations at conferences, and publication in a scientific journal. Ethics approval is not required.
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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 | 0.095 | 0.077 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".