Migrant Social Workers, Foreign Credential Recognition and Securing Employment in Canada
Bibliographic record
Abstract
Canada is a culturally diverse receiving country for transnational migration, and social workers are among the professional migrants who arrive in Canada each year. This article draws on findings from a four-year, grounded theory study on the professional adaptation processes and experiences of migrant social workers (n = 66) in the Canadian context. Study findings highlight a range of internal (personal) attributes and external (contextual) elements that interact to serve as either protective or vulnerabilizing factors during the pre-employment phase of professional adaptation. The focus of this article is to describe the interactions of protective and vulnerabilizing factors associated with the experience of obtaining recognition of foreign credentials and securing employment as a social worker in Canada. The findings demonstrate that migrant social workers in Canada face significant barriers in these two pre-employment phases of professional adaptation. A range of research and policy implications is identified. In particular, we highlight the disconnect that exists between Canada’s migration-friendly policies, and the lack of organizational and governmental supports and services to facilitate successful labour market integration of migrant social workers.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".