Push, pull, and plant: the personal side of physician immigration to alberta, Canada.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The global migration of physicians has led many international physicians to enter practice in Alberta, Canada. The study was designed to explore the personal side of migration and transition experiences of these international medical graduates (IMGs). METHODS: A qualitative study using telephone interviews and a semi-structured interview guide was used to interview 19 IMGs who are currently practicing and have held Part V, restricted or temporary practice licenses for less than 7 years. RESULTS: Three major themes were identified. The first was the "push" from their own country of origin and their perception that moving to Alberta would be better for them. Professional opportunities in their home country had been affected by changing policies, lack of infrastructure, and personal/family safety issues culminating in highly stressful work environments. The second was "pull." An improvement in the quality of personal life was associated with geographical, educational, recreational, and spiritual aspects of daily living for participants and their families in their new environment. The third theme was "plant"ie, factors that encouraged them to stay in Alberta. CONCLUSIONS: This study demonstrates the continued relevance of push and pull theory in understanding IMG physician migration. Our findings in this study indicate that remaining in place, or "being planted" is conditional on political, social, and economic aspects.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".