Overqualified or Underwanted? A Critical Examination of Skilled Immigrant Deskilling Among Racialized Immigrants in Toronto and Vancouver
Bibliographic record
Abstract
Recent research on immigrant employment and integration into Canadian society reveals that although economic integration of immigrants has always been held as the key to successful settlement, a gap exists between immigrant skill sets and their employment realities once in Canada. Economic class immigrants chosen from the Federal Skilled Workers Programs are identified as the most likely to succeed since they have been evaluated according to human capital discourses. How do they fare once admitted? This paper explores the social issue of skilled immigrants’ barriers upon entering the Canadian labour market and how a racialized labour force has been constructed and perpetuated. Particular focus is on the requirement of “Canadian experience,” as foreign work and education experiences has been devalued, leading to immigrant deskilling in the workforce. This paper reviewed literature which focuses on racialized skilled immigrants’ structural barriers when finding employment, and it is argued by the researchers that deskilling is one of the ways in which Canada, while maintaining multiculturalism on the surface, goes on to perpetuate a racist status quo in which immigrants are trapped in the bottom of a two-tier labour system. For possible solutions, the paper links the issue of skilled immigrant employment with anti-oppressive social work practices when engaging with immigrant communities. The incorporation of anti-oppressive practices when working with racialized skilled immigrant populations can allow change to happen at macro and micro levels, through identifying barriers as systemic and socially constructed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".