Growing up Canadian: language, culture, and identity among second-generation Chinese youths in Canada
Bibliographic record
Abstract
This dissertation empirically describes the emerging patterns of incorporation in terms of language, culture, and identity among second-generation Chinese youths growing up in Canada. The theoretical focus of my study is to (1) identify the limitations of conventional assimilation theory and (2) explore the applicability of “segmented assimilation theory” in studying the second-generation incorporation in Canada. In addition, in order to understand the mechanism by which non zero-sum bicultural form of adaptation becomes prevalent among the contemporary second-generation youths, I pay special attention to the role of ethnic socialization by parents and friends as well as network variety of friends. The findings suggest that the patterns and extent of incorporation vary among second-generation Chinese youths in Canada; conventional assimilation theory cannot fully explain this variation. In terms of language, the rate and the patterns of the shift toward English monolingualism depend on the interactive effect of parental socioeconomic resources and community context, as suggested in segmented assimilation theory. Those children from lower income families in cities with a higher Chinese immigrant concentration tend to show a selective mode of acculturation. Children from higher income families will become English monolinguals at a higher rate regardless of community context. In terms of culture, the current study also finds that acculturation does not necessarily take place at the expense of ethnic culture as suggested in conventional assimilation theory. As long as second-generation youths are surrounded by parents and friends who can influence their ethnic retention, their incorporation can take place in an additive and bicultural form. The results strongly suggest that cultural incorporation is a network mediated process and we need to look at social relations in which the second-generation youths are embedded in order to understand the persistence of biculturalism. In terms of identity, the results show that there is a manifestation of binational hyphenated-Canadian identity among the second-generation Chinese.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".