To stay or not to stay: the role of sense of belonging in the retention of physicians in rural areas
Bibliographic record
Abstract
Rural communities across the circumpolar region and worldwide perennially suffer from physician shortages despite decades of attempting targeted strategies for recruitment. Particularly in rural Canada, financial incentives have attracted but not retained a medical workforce. Although the importance of social connection or belonging is a long-established source of well-being, such information has not infiltrated the dialogue or action on physician retention in rural areas. A physician's sense of belonging, arising from that emotional need for social connectedness, is built via bilateral active efforts at community engagement, reciprocity, social integration of family and workplace collegiality. Links between rural upbringing, rural training opportunities and subsequent rural practice likely rest upon fostering this sense of belonging. Policymakers and recruiters might consider how to help physicians adapt, "fit in", and consider they have "come home" when they venture off to rural settings. Empowering the community to be involved in the recruitment and retention of rural physicians may also be effective. Perhaps this approach would better address the age-old battle to retain physicians in rural Canada and around the world.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".