Defining the Canadian rural general surgeon
Bibliographic record
Abstract
BACKGROUND: A total of 18%-30% of Canadians live in a rural area and are served by 8% of the country's general surgeons. The demographic characteristics of Canada's population and its geography greatly affect the health outcomes and needs of the population living in rural areas, and rural general surgeons hold a unique role in meeting the surgical needs of these communities. Rural general surgery is a distinct area of practice that is not well understood. We aimed to define the Canadian rural general surgeon to inform rural health human resource planning. METHODS: A scoping review of the literature was undertaken of Ovid, MEDLINE, and Embase using the terms "rural," "general surgery," and "workforce." We limited our review to articles from North America and Australia. RESULTS: The search yielded 425 titles, and 110 articles underwent full-text review. A definition of rural general surgery was not identified in the Canadian literature. Rurality was defined by population cut-offs or combining community size and proximity to larger centres. The literature highlighted the unique challenges and broad scope of rural general surgical practice. CONCLUSION: Rural general surgeons in Canada can be defined as specialists who work in a small community with limited metropolitan influence. They apply core general surgery skills and skills from other specialties to serve the unique needs of their community. Surgical training programs and health systems planning must recognize and support the unique skill set required of rural general surgeons and the critical role they play in the health and sustainability of rural communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".