The Construction of the Skilled and Healthy Immigrant
Bibliographic record
Abstract
The purpose of this study is to explore how skilled racialized immigrants (SRIs) make sense of their well-being when they immigrate to Canada under the Federal Skilled Workers Program (FSWP). To fulfill this purpose, I used an Interpretative Phenomenological Analysis (IPA) to conduct 12 qualitative semi-structured interviews with individuals who self-identified as skilled racialized immigrants. IPA is a useful research method to explore the interpretations and meanings that participants give to the phenomena of well-being. IPA fits with my epistemological and ontological perspective that skilled racialized immigrants are the true experts of their lives. Since knowledge is socially constructed, governed by power relations, and contextually bound, a decolonizing theoretical orientation is well suited to explore this topic area. The findings reveal that the participants are forced to start from scratch in Canada, since they struggled to have their credentials recognized here. An intersectional lens is particularly useful for this study, as it uncovers the different experiences of the participants. The participants do not perceive themselves as passive victims of intersectional oppression, colonial racism, and othering practices. Rather, they are active agents of social change, as they disrupt and resist the oppression they encounter in society. Furthermore, the participants were critical of the FSWP, since for most their dream of working in their field in Canada turned out to be a nightmare. The thesis findings contribute to the field of mental health, immigration, and employment, for there is a scarcity of literature that discusses the impact of social and structural determinants of health on skilled racialized immigrants in Canada. The thesis concludes with recommendations and implications for social work education, practice, and policy.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.046 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| 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".