Theorizing the barriers and facilitators to relicensing and resettling of Albertan International Medical Graduates
Bibliographic record
Abstract
The purpose of this qualitative research study was to explore how Albertan International Medical Graduates (AIMGs) negotiated barriers and facilitators during their journey to Canadian medical licensure by incorporating the views and perceptions of two study groups: practicing and non-practicing. This research used Charmaz’s (2014) constructivist grounded theory approach and was informed by six non-practising and seven practising AIMGs. The participants were individually interviewed with open-ended, in-depth questions. This research provided rich insight into the Canadian medical licensure experiences of AIMGs. Seven key factors to the successful licensure of AIMGs were identified: finances, language, family, culture, networks, institutional rules, and intrapersonal characteristics. A theoretical framework was developed to explain how AIMGs negotiated those factors to obtain their Canadian medical license. Furthermore, acculturation theory was used to explain the acculturation strategies of AIMGs, and institutional theory was used to explain how the existing policies and regulations acted as barriers to the licensing of AIMGs. AIMGs used two acculturation strategies, integration was the preferred choice of adaptation to the Canadian society, and assimilation was the only possibility when adapting to the hospital culture. Health care administrators and policy makers can use the concepts identified in this study to integrate more AIMGs into the Canadian health care system.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".