The changing face of work and learning in the context of immigration: the Canadian experience
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
Through the accounts of the experience of recent Chinese immigrants in Canada, this study examines the changing nature of work and learning in the context of immigration. Its findings reveal the precarious nature of work and learning for immigrant professionals, characterised by part time, low wages, job insecurity, high risks of ill health and limited social benefits and statutory entitlements. The study also shows that immigrants’ foreign credentials and knowledge have been racialised on the basis of ethnic and national origins. As a consequence, they suffered unemployment and underemployment, poor economic performance and downward social mobility. The racialised experience of Chinese immigrants demonstrates how racial and socio-cultural differences have been used to entrench social inequality in immigrants’ transitions. Through the process of deskilling and re-skilling, learning has become a vehicle to colonising immigrants into the dominant norms and values of the host society. The study urges government organisations, professional associations, educational institutions and prior learning assessment agencies to adopt an inclusive framework which fully embraces all human knowledge and experience, no matter which ethnic and cultural backgrounds they emerge from.
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 | 0.001 | 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