Bibliographic record
Abstract
This dissertation explores the interplay between language, religion and immigrant settlement in globalization, using skilled Chinese immigrants in Toronto, Canada as a case. The analytical framework combines social culturally sensitive approaches to learning (Vygotsky 1978; Lave and Wenger 1991; Lantolf 2000b) and language (Bourdieu 1977a, 1977b, 1991; Woolard 1998), and situates immigrants' "language problem" within applied linguistics, but more importantly in the globalized political economy (Heller 2003). This dissertation questions the assumption that linguistic proficiency is the key to economic, social and political integration, an assumption that underlies Canadian immigrant selection and settlement service provision policies. It suggests that social economic inclusion, or allowing ethnolinguistic minority immigrants a legitimate speaking position, at interpersonal, institutional and ideological levels, is the condition and process of immigrant language learning. The dissertation results from a three-year ethnography of the settlement experiences and trajectories of five immigrants who had worked professionally in Mainland China prior to immigration, including interviews with twenty-two people who were influential in their settlement. It focuses on one couple and documents their lived experiences of finding access to learning English, searching for work in their fields, struggling to settle, and becoming devoted evangelical Christians in Toronto. It examines their language practices and identity reconstruction at three strategic sites: a community college and two churches. It shows that the formal English classes constructed the couple as language learners who were necessarily deficient, and thus did not offer them a position from which to speak legitimately. Positioned as outsiders and having little idea of how to shift to the 'inside', they experienced alienation. In contrast, the interpersonal support and more inclusive structure and ideology at church allowed them to progressively participate in informal and/or formal church activities, thus offered them a legitimate speaking position. Evangelical Christianity also provided them a framework to interpret their immigration and settlement experiences as ethnolinguistic minorities in Canada. Their increased participation at church constituted a gendered process of improving English, finding pathways into social and economic life, and becoming integrated into a transnational evangelical Christian Chinese community.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 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".