Inequitable treatment as perceived by international medical graduates (IMGs): a scoping review
Bibliographic record
Abstract
OBJECTIVES: This scoping review seeks to detail experiences of inequitable treatment, as self-reported by international medical graduates (IMGs), across time and location. DESIGN: Scoping review. SEARCH STRATEGY: Three academic medical databases (MEDLINE, SCOPUS and PSYCINFO) and grey literature (GOOGLE SCHOLAR) were systematically searched for studies reporting first-hand IMG experiences of perceived inequitable treatment in the workplace: discrimination, prejudice or bias. Original (in English) qualitative, quantitative, mixed studies or inquiry-based reports from inception until 31 December 2022, which documented direct involvement of IMGs in the data were eligible for inclusion in the review. Systematic reviews, scoping reviews, letters, editorials, news items and commentaries were excluded. Study characteristics and common themes were identified and analysed through an iterative process. RESULTS: We found 33 publications representing 31 studies from USA, Australia, UK, Canada, Germany, Finland, South Africa, Austria, Ireland and Saudi Arabia, published between 1982 and 2022. Common themes identified by extraction were: (1) inadequate professional recognition, including unmatched assigned work or pay; (2) perceived lack of choice and opportunities such as limited freedoms and perceived control over own future; (3) marginalisation-subtle interpersonal exclusions, stereotypes and stigma; (4) favouring of local graduates; (5) verbal insults, culturally or racially insensitive or offensive comments; and (6) harsher sanctions. Other themes identified were effects on well-being and proposed solutions to inequity. CONCLUSIONS: This study found evidence that IMGs believe they are subject to numerous common inequitable workplace experiences and that these experiences have self-reported repercussions on well-being and career trajectory. Further research is needed to substantiate correlations and causality in relation to outcomes of well-being and differential career attainment. Furthermore, research into support for IMGs and the creation of more equitable workforce environments is also recommended.
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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 | 0.021 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 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".