A scoping review of refugees’ employment integration experience and outcomes in Canada
Bibliographic record
Abstract
BACKGROUND: Refugees involuntarily arrive to Canada to escape unfavourable conditions in their home country. Employment is an important marker of integration and a foundational determinant of health yet; little is known about the employment integration experiences of refugees as a distinct group of workers in Canada. OBJECTIVE: This scoping review was completed to explore the employment experience and outcomes of refugees in Canada and to identify gaps in the literature. METHODS: Three databases were searched for peer-reviewed articles published in English over a 25-year period, 1993 to 2018, for research on refugees and employment in the Canadian context. The research team reviewed all articles, including abstract screening, full text review and data extraction; consensus on inclusion was reached for all articles. Relevant articles were synthesized for overarching themes. RESULTS: The search strategy identified 2,723 unique articles of which 16 were included in the final sample. There was a mix of quantitative, qualitative and mixed-methods studies which reported on employment rates of refugees, the quality of jobs secured, gendered differences in employment experience and differential impacts of under/unemployment on health and well-being. CONCLUSION: The findings suggest that refugees in Canada do not secure jobs that are in line with their previous skills and experience leading to downward occupational mobility and poorer health with refugee women experiencing these outcomes more acutely. Research in this area with long-term outcomes and contextualized experiences is needed, as well as studies that include equity considerations such as racialization and gender.
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 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 | 0.018 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.036 | 0.061 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".