Doubly precarious immigrant academics: professional identities and work integration of a highly skilled precariat in Canadian higher education
Bibliographic record
Abstract
Purpose Educational institutions are investing heavily in the internationalization of their campuses to attract global talent. Yet, highly skilled immigrants face persistent labor market challenges. We investigate how immigrant academics experience and mitigate their double precarity (migrant and academic) as they seek employment in higher education in Canada. Design/methodology/approach We take a phenomenological approach and draw on reflective interviews with nine immigrant academics, encouraging participants to elaborate on symbols and metaphors to describe their experiences. Findings We found that immigrant academics constitute a unique highly skilled precariat: a group of professionals with strong professional identities and attachments who face the dilemma of securing highly precarious employment (temporary, part-time and insecure) in a new academic environment or forgoing their professional attachment to seek stable employment in an alternate occupational sector. Long-term, stable and commensurate employment in Canadian higher education is out of reach due to credentialism. Those who stay the course risk deepening their precarity through multiple temporary engagements. Purposeful deskilling toward more stable employment that is disconnected from their previous educational and career accomplishments is a costly alternative in a situation of limited information and high uncertainty. Originality/value We bring into the conversation discussions of migrant precarity and academic precarity and draw on immigrant academics’ unique experiences and strategies to understand how this double precarization shapes their professional identities, mobility and work integration in Canadian higher education.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".