The attractiveness of return-for-service bursary programs to medical students in Newfoundland and Labrador
Bibliographic record
Abstract
Objectives and Methods: This study compared Return-for-service (RFS) programs available from provincial/territorial governments, determined terms of interest and predictors of acceptance in Newfoundland and Labrador (NL), and described experiences of RFS-holders. Research methods included document analysis, an online survey, and telephone interviews. -- Results: RFS programs were a poplar means of improving physician distribution. -- Students rated monetary value (37.3%) and location of service return (34.9%) as the most important features in their decision to accept an RFS. Trainees with financial concerns and those who planned to remain in NL were 4.8 and 27.7 times more likely to accept a bursary. -- Experiences of RFS-holders were positive; communication difficulties and a lack of active recruitment were identified as problems. -- Conclusions: The RFS shows some promise for increasing physician recruitment, however it does not appear to be the most effective means; more bursaries fund trainees who plan to remain in NL already (80%) than attracts novel trainees (20%).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".