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Record W4318475725 · doi:10.3390/ijerph20032311

Alternative Careers toward Job Market Integration: Barriers Faced by International Medical Graduates in Canada

2023· article· en· W4318475725 on OpenAlexaffabout
Tanvir Chowdhury Turin, Nashit Chowdhury, Deidre Lake

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsAlberta Medical AssociationUniversity of Calgary
Fundersnot available
KeywordsJob marketMedical educationPsychologyBusinessMedicineEngineeringWork (physics)Mechanical engineering

Abstract

fetched live from OpenAlex

International Medical Graduates (IMGs), who completed their medical degree and training outside Canada constitute a notable portion of the skilled migrants of the country. However, due to a long and uncertain licensure process and limited opportunities many IMGs look for alternative career pathways where they can utilize their learned skills. Alternative careers in the health and wellness sector may offer such opportunities; however, IMGs' success in these pathways were also less evident despite their high potential. In this study, we investigated the barriers that IMGs stated to face when attempting alternative jobs in Canada. Eight focus groups with 42 IMGs in Canada were conducted. Using a thematic analysis approach, we identified that IMGs encounter these barriers in different stages of their resettlement journey in Canada, including both the pre-migration and post-migration phases. In the pre-migration phase, IMGs were not aware of the success rates of the licensing pathways and did not have sufficient information regarding potential alternative careers. In the post-migration phase, the lack of information continues to affect IMGs where IMGs exhaust their resources pursuing alternative careers without proper guidance and support. Further, IMGs struggle with taking preparation for alternative careers by obtaining further certifications and completing other prerequisites for some barriers, such as financial constraints. While looking for jobs, some IMGs perceived systemic discrimination such as non-recognition of their credentials and experience. Furthermore, the mismatch of expectations and limited growth opportunities offered by potential careers serve to disincentivize IMGs from pursuing an alternative career. Addressing the current employment inequity experienced by IMGs in Canada warrants research collaborations between organizations supporting IMGs and policymakers that target known barriers to the pursuit of alternative careers by IMGs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.089
GPT teacher head0.457
Teacher spread0.368 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2023
Admission routes2
Has abstractyes

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