The implications of being an international medical graduate (IMG) in Canadian society : a qualitative study of foreign-trained physicians' resettlement, sense of identity and health status
Bibliographic record
Abstract
This qualitative research study used grounded theory methodology to explore the \nsettlement experiences and changes in professional identity, self esteem and health status \nof foreign-trained physicians (FTPs) who resettled in Canada and were not able to \npractice their profession. Seventeen foreign-trained physicians completed a pre-survey \nand rated their health status, quality of life, self esteem and stress before and after coming \nto Canada. They also rated changes in their experiences of violence and trauma, \ninclusion and belonging, and racism and discrimination. Eight FTPs from the survey \nsample were interviewed in semi-structured qualitative interviews to explore their \nexperiences with the loss of their professional medical identities and attempts to regain \nthem during resettlement. \nThis study found that without their medical license and identity, this group of \nFTPs could not fully restore their professional, social, and economic status and this \naffected their self esteem and health status. The core theme of the loss of professional \nidentity and attempts to regain it while being underemployed were connected with the \nmultifaceted challenges of resettlement which created experiences of lowered selfesteem, \nand increased stress, anxiety and depression. They identified the re-licensing \nprocess (cost, time, energy, few residency positions, and low success rate) as the major \nbarrier to a full and successful settlement and re-establishment of their identities. \nGrounded research was used to develop General Resettlement Process Model and \na Physician Re-licensing Model outlining the tasks and steps for the successfiil general \nresettlement of all newcomers to Canada with additional process steps to be \naccomplished by foreign-trained physicians. Maslow's Theory of Needs was expanded \nto include the re-establishment of professional identity for this group to re-establish levels \nof safety, security, belonging, self-esteem and self-actualization. \nForeign-trained physicians had established prior professional medical identities, \nself-esteem, recognition, social status, purpose and meaning and bring needed human \ncapital and skills to Canada. However, without identifying and addressing the barriers to \ntheir full inclusion in Canadian society, the health of this population may deteriorate and \nthe health system of the host country may miss out on their needed contributions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".