Students Who Stay: Stories of Northern Medical Program Graduates and Place Integration.
Bibliographic record
Abstract
Canada's persistent nationwide physician shortage is further complicated in remote, rural, and northern areas because a considerable majority of Canadian physicians choose to practice in larger urban centres, leaving many sparsely populated communities with inadequate access to physicians. Research into physician maldistribution clearly shows that increasing the supply of medical graduates alone will not improve the situation in rural and remote Canada. In addition to recruitment, processes that contribute to retention must be considered and integrated into strategies aimed at reducing physician maldistribution. There remains a lack of knowledge about the unique experiences of students who train in northern British Columbia (BC). The purpose of this research is to better understand the significant, influential, and transformational experience of northern BC-trained medical students and new physicians in order to better support northern communities in retaining a sustainable physical workforce. Qualitative data from interviews with seven NMP graduates currently practicing medicine in northern BC were analyzed. Strong themes related to students' backgrounds, characteristics of community, and experiences throughout their time in the NMP suggest that the evolution of individuals' attitudes and decisions prior to arriving in a community influence their ongoing process of integration and retention in place. --Leaf ii.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.014 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".