The Migration of South African Graduates to Canada: a Survey of Medical Practitioners in Saskatchewan
Bibliographic record
Abstract
Aim of study: To determine the socio-demographic profile of South African doctors who have permanently emigrated to Saskatchewan, Canada, and to find out why they left, how they have adapted and if they intend returning to South Africa. Study design: A cross-sectional postal survey. Method: All South African qualified medical practitioners in Saskatchewan with permanent registration (N=218) were mailed anonymity-assure questionnaires. A second mailing was sent to non-respondents. Results: A 59% (N = 107) response was elicited with 35 returned-to-sender. Most doctors (79%) had left South Africa after 1990. Most (58%) qualified at Afrikaans medium medical schools in South Africa. The male to female ratio was 88:12. Seventy-four percent (74%) of respondents were general practitioners. Prior to emigration, 67% of respondents were employed in the South African public service. Most doctors (59%) earned between R525 000 and R876 000 per year in Canada. Violence was the most important reason for leaving South Africa, followed by perceived economic problems in South Africa and adverse working conditions at State health facilities. Adaptation and positive adjustments in a newly acquired country and lifestyle were evident. Returning to South Africa does not seem likely unless crime and violence diminish substantially. Conclusion: Most emigrants were male, recently qualified from all the major medical schools in South Africa, with equal Afrikaans and English speaking proportions. They left mainly because of fear for their personal security and poor working conditions in the South African public health sector. They are well settled in their new country, earn above average incomes in Canada and are very unlikely to return.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.003 | 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".