Immigration, Literacy, and Mobility: A Critical Ethnographic Study of Well-educated Chinese Immigrantsâ Trajectories in Canada
Bibliographic record
Abstract
This dissertation interrogates the deficit assumptions about English proficiency of skilled immigrants who were recruited by Canadian governments between the late 1990s and early 2000s. Through the lens of literacy as social practice, the eighteen-month ethnographic qualitative research explores the sequential experiences of settlement and economic integration of seven well-educated Chinese immigrant professionals. The analytical framework is built on sociocultural approaches to literacy and learning, as well as the theories of discourses and language reproduction. Using multiple data sources (observations, conversational interviews, journal and diary entries, photographs, documents, and artifacts collected in everyday lives), I document many different ways that well-educated Chinese immigrants take advantage of their language and literacy skills in English across several social domains of home, school, job market, and workplace. \nExamining the trans-contextual patterning of the participants’ language and literacy activities reveals that immigrant professionals use literacy as assistance in seeking, negotiating, and taking hold of resources and opportunities within certain social settings. However, my data show that their language and literacy engagements might not always generate positive consequences for social networks, job opportunities, and upward economic mobility. Close analyses of processes and outcomes of the participants’ engagements across these discursive discourses make it very clear that the monolithic assumptions of the dominant language shape and reinforce structural barriers by constraining their social participation, decision making, and learning practice, and thereby make literacy’s consequences unpredictable. The deficit model of language proficiency serves the grounds for linguistic stereotypes and economic marginalization, which produces profoundly consequential effects on immigrants’ pathways as they strive for having access to resources and opportunities in the new society. \nMy analyses illuminate the ways that language and literacy create the complex web of discursive spaces wherein institutional agendas and personal desires are intertwined and collide in complex ways that constitute conditions and processes of social and economic mobility of immigrant populations. Based on these analyses, I argue that immigrants’ successful integration into a host country is not about the mastery of the technical skills in the dominant language. Rather, it is largely about the recognition and acceptance of the value of their language use and literacy practice as they attempt to partake in the globalized new economy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.029 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".