‘Survival Employment’: Gender and Deskilling among African Immigrants in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Recent research points to a growing gap between immigrant and native‐born outcomes in the Canadian labour market at the same time as selection processes emphasize recruiting highly educated newcomers. Drawing on interviews with well‐educated men and women who migrated from countries in sub‐Saharan Africa, this paper explores the gendered processes that produce weak economic integration in Canada. Three‐quarters of research participants experienced downward occupational mobility, with the majority employed in low‐skilled, low‐wage, insecure forms of “survival employment”. In a gendered labour market, where common demands for “Canadian experience”, “Canadian credentials” and “Canadian accents” were uneven across different sectors of the labour market, women faced particular difficulties finding “survival employment”; in the long run, however, women’s greater investment in additional post‐secondary education within Canada placed them in a somewhat better position than men. The policy implications of this study are fourfold: first, we raise questions about the efficacy of Canadian immigration policies that prioritize the recruitment of well‐educated immigrants without addressing the multiple barriers that result in deskillling; second, we question government policies and settlement practices that undermine more equitable economic integration of immigrants; third, we address the importance of tackling the “everyday racism” that immigrants experience in the Canadian labour market; and finally, we suggest the need to re‐think narrowly defined notions of economic integration in light of the gendered nature of contemporary labour markets, and immigrants’ own definitions of what constitutes meaningful integration.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it