First language maintenance and attrition among young Chinese adult immigrants: a multi-case study
Bibliographic record
Abstract
The role of the first language (L1) has been generally acknowledged as having important implications for young immigrants’ linguistic, educational, socio-cultural, intellectual, career, and identity development (e.g., Cummins, 2001; Guardado, 2002; Kim 2006; Kouritzin, 1999). In this case study I investigated the first language maintenance and attrition of three young adults who had immigrated to Canada as children from mainland China and Taiwan. Two questions were addressed: (a) What linguistic elements were maintained and eroded in the participants’ heritage language? and (b) What social and psychological factors contributed to the participants’ L1 maintenance and attrition? The data were collected through self-evaluation questionnaires, translation tasks and open-ended interviews both in English and Mandarin. Using a combination of life stories describing the participants’ personal linguistic and social experiences in Canada and the results of linguistic assessments through different tasks, the study provides a detailed examination of the phenomenon of L1 maintenance and attrition among young adult immigrants from China. The findings of this study indicate that the three participants took distinct routes resulting in differential outcomes in their first language maintenance and attrition. Ethnic and cultural identity, and language attitudes and beliefs were identified as important internal factors. School discourse including teachers’ attitudes towards immigrants’ L1, peer influences and access to planned L1 educational activities both at home and in the school system were important external factors affecting the participants’ L1 maintenance and attrition. The results provide support for the view that a collaborative, inclusive approach to education that involves not only immigrant students, but also their families, educational systems, and society in general facilitates young immigrants’ bilingualism and acculturation.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".